--- title: MiniMax M2.5 | Runware Docs url: https://runware.ai/docs/models/minimax-m2-5 description: State-of-the-art agentic coding and office-work model, optimized for speed and cost --- # MiniMax M2.5 MiniMax-M2.5 is MiniMax’s latest frontier model, optimized for fast, low-cost agentic workflows across coding, search/tool use, and high-value office tasks. Trained with large-scale reinforcement learning in complex real-world environments, it delivers strong reasoning, efficient task decomposition, and high-quality outputs for production assistants and enterprise workflows. - **ID**: `minimax:m2.5@0` - **Status**: live - **Creator**: MiniMax - **Release Date**: February 12, 2026 - **Capabilities**: Text to Text ## Pricing - **Input tokens / 1M**: `$0.27` - **Output tokens / 1M**: `$0.95 / 1M` ## Request Parameters **API Options** Platform-level options for task execution and delivery. ### [taskType](https://runware.ai/docs/models/minimax-m2-5#request-tasktype) - **Type**: `string` - **Required**: true - **Value**: `textInference` Identifier for the type of task being performed ### [taskUUID](https://runware.ai/docs/models/minimax-m2-5#request-taskuuid) - **Type**: `string` - **Required**: true - **Format**: `UUID v4` UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task. ### [webhookURL](https://runware.ai/docs/models/minimax-m2-5#request-webhookurl) - **Type**: `string` - **Format**: `URI` Specifies a webhook URL where JSON responses will be sent via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available. **Learn more** (1 resource): - [Webhooks](https://runware.ai/docs/platform/webhooks) (platform) ### [deliveryMethod](https://runware.ai/docs/models/minimax-m2-5#request-deliverymethod) - **Type**: `string` - **Default**: `sync` Determines how the API delivers task results. **Allowed values**: - `sync` Returns complete results directly in the API response. - `async` Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse. - `stream` Streams results token-by-token as they are generated. **Learn more** (1 resource): - [Task Polling](https://runware.ai/docs/platform/task-polling) (platform) ### [includeCost](https://runware.ai/docs/models/minimax-m2-5#request-includecost) - **Type**: `boolean` - **Default**: `false` Include task cost in the response. ### [includeUsage](https://runware.ai/docs/models/minimax-m2-5#request-includeusage) - **Type**: `boolean` - **Default**: `false` Include token usage statistics in the response. ### [splitThinking](https://runware.ai/docs/models/minimax-m2-5#request-splitthinking) - **Type**: `boolean` - **Default**: `false` When enabled, the model's internal reasoning is separated from the main response and returned in a dedicated `reasoningContent` field. ### [numberResults](https://runware.ai/docs/models/minimax-m2-5#request-numberresults) - **Type**: `integer` - **Min**: `1` - **Max**: `4` - **Default**: `1` Number of results to generate. Each result uses a different seed, producing variations of the same parameters. **Generation Parameters** Core parameters for controlling the generated content. ### [model](https://runware.ai/docs/models/minimax-m2-5#request-model) - **Type**: `string` - **Required**: true - **Value**: `minimax:m2.5@0` Identifier of the model to use for generation. **Learn more** (3 resources): - [Text To Image: Model Selection The Foundation Of Generation](https://runware.ai/docs/guides/text-to-image#model-selection-the-foundation-of-generation) (guide) - [Image Inpainting: Model Specialized Inpainting Models](https://runware.ai/docs/guides/image-inpainting#model-specialized-inpainting-models) (guide) - [Image Outpainting: Other Critical Parameters](https://runware.ai/docs/guides/image-outpainting#other-critical-parameters) (guide) ### [seed](https://runware.ai/docs/models/minimax-m2-5#request-seed) - **Type**: `integer` - **Min**: `0` - **Max**: `4294967295` Random seed for reproducible generation. When not provided, a random seed is generated in the unsigned 32-bit range. ### [messages](https://runware.ai/docs/models/minimax-m2-5#request-messages) - **Path**: `messages.role` - **Type**: `array of objects (2 properties)` - **Required**: true Array of chat messages forming the conversation context. #### [role](https://runware.ai/docs/models/minimax-m2-5#request-messages-role) - **Path**: `messages.role` - **Type**: `string` - **Required**: true The role of the message author. **Allowed values**: `user` `assistant` #### [content](https://runware.ai/docs/models/minimax-m2-5#request-messages-content) - **Path**: `messages.content` - **Type**: `string` - **Required**: true - **Min**: `1` The text content of the message. **Settings** Technical parameters to fine-tune the inference process. These must be nested inside the \`settings\` object. ### [systemPrompt](https://runware.ai/docs/models/minimax-m2-5#request-settings-systemprompt) - **Path**: `settings.systemPrompt` - **Type**: `string` - **Min**: `1` - **Max**: `200000` System-level instruction that guides the model's behavior and output style across the entire generation. ### [temperature](https://runware.ai/docs/models/minimax-m2-5#request-settings-temperature) - **Path**: `settings.temperature` - **Type**: `float` - **Min**: `0` - **Max**: `2` - **Step**: `0.01` - **Default**: `1` Controls randomness in generation. Lower values produce more deterministic outputs, higher values increase variation and creativity. ### [topP](https://runware.ai/docs/models/minimax-m2-5#request-settings-topp) - **Path**: `settings.topP` - **Type**: `float` - **Min**: `0` - **Max**: `1` - **Step**: `0.01` - **Default**: `0.95` Nucleus sampling parameter that controls diversity by limiting the probability mass. Lower values make outputs more focused, higher values increase diversity. ### [frequencyPenalty](https://runware.ai/docs/models/minimax-m2-5#request-settings-frequencypenalty) - **Path**: `settings.frequencyPenalty` - **Type**: `float` - **Min**: `0` - **Max**: `2` - **Step**: `0.01` - **Default**: `0` Penalizes tokens based on their frequency in the output so far. A value of 0.0 disables the penalty. ### [maxTokens](https://runware.ai/docs/models/minimax-m2-5#request-settings-maxtokens) - **Path**: `settings.maxTokens` - **Type**: `integer` - **Min**: `1` - **Max**: `196608` - **Default**: `8192` Maximum number of tokens to generate in the response. ### [minP](https://runware.ai/docs/models/minimax-m2-5#request-settings-minp) - **Path**: `settings.minP` - **Type**: `float` - **Min**: `0` - **Max**: `1` - **Step**: `0.01` - **Default**: `0` Minimum probability threshold. Tokens with probability below this value are excluded from sampling. ### [presencePenalty](https://runware.ai/docs/models/minimax-m2-5#request-settings-presencepenalty) - **Path**: `settings.presencePenalty` - **Type**: `float` - **Min**: `0` - **Max**: `2` - **Step**: `0.01` - **Default**: `0` Encourages the model to introduce new topics. A value of 0.0 disables the penalty. ### [repetitionPenalty](https://runware.ai/docs/models/minimax-m2-5#request-settings-repetitionpenalty) - **Path**: `settings.repetitionPenalty` - **Type**: `float` - **Min**: `0` - **Max**: `2` - **Step**: `0.01` - **Default**: `1` Penalizes tokens that have already appeared in the output. A value of 1.0 disables the penalty. ### [stopSequences](https://runware.ai/docs/models/minimax-m2-5#request-settings-stopsequences) - **Path**: `settings.stopSequences` - **Type**: `array of strings` - **Min**: `1` Array of sequences that will cause the model to stop generating further tokens when encountered. ### [topK](https://runware.ai/docs/models/minimax-m2-5#request-settings-topk) - **Path**: `settings.topK` - **Type**: `integer` - **Min**: `1` - **Max**: `100` - **Default**: `40` Top-K sampling parameter that limits the number of highest-probability tokens considered at each step. ## Response Parameters ### [taskType](https://runware.ai/docs/models/minimax-m2-5#response-tasktype) - **Type**: `string` - **Required**: true - **Value**: `textInference` Type of the task. ### [taskUUID](https://runware.ai/docs/models/minimax-m2-5#response-taskuuid) - **Type**: `string` - **Required**: true - **Format**: `UUID v4` UUID of the task. ### [text](https://runware.ai/docs/models/minimax-m2-5#response-text) - **Type**: `string` - **Required**: true Generated text content. ### [reasoningContent](https://runware.ai/docs/models/minimax-m2-5#response-reasoningcontent) - **Type**: `string` The model's internal reasoning content, separated from the main response. Only present when `splitThinking` is enabled. ### [cost](https://runware.ai/docs/models/minimax-m2-5#response-cost) - **Type**: `float` Task cost in USD. Present when `includeCost` is set to `true` in the request. ### [finishReason](https://runware.ai/docs/models/minimax-m2-5#response-finishreason) - **Type**: `string` - **Required**: true The reason why the model stopped generating tokens. **Possible values**: `stop` `length` `content_filter` `unknown` ### [usage](https://runware.ai/docs/models/minimax-m2-5#response-usage) - **Path**: `usage.promptTokens` - **Type**: `object (4 properties)` - **Required**: true Token usage statistics for the request. #### [promptTokens](https://runware.ai/docs/models/minimax-m2-5#response-usage-prompttokens) - **Path**: `usage.promptTokens` - **Type**: `integer` - **Required**: true - **Min**: `0` Number of tokens in the input prompt. #### [completionTokens](https://runware.ai/docs/models/minimax-m2-5#response-usage-completiontokens) - **Path**: `usage.completionTokens` - **Type**: `integer` - **Required**: true - **Min**: `0` Number of tokens generated in the response. #### [totalTokens](https://runware.ai/docs/models/minimax-m2-5#response-usage-totaltokens) - **Path**: `usage.totalTokens` - **Type**: `integer` - **Required**: true - **Min**: `0` Total number of tokens used (prompt + completion). #### [thinkingTokens](https://runware.ai/docs/models/minimax-m2-5#response-usage-thinkingtokens) - **Path**: `usage.thinkingTokens` - **Type**: `integer` - **Min**: `0` Number of tokens used for internal reasoning. Billed separately. ## Examples ### Midnight Logistics Crisis Memo (Text to Text) **Request**: ```json { "taskType": "textInference", "taskUUID": "653b1cb1-58a7-4c5a-b3fd-a75a7345684c", "model": "minimax:m2.5@0", "seed": 32945, "settings": { "systemPrompt": "You are a sharp enterprise operations assistant. Synthesize incomplete information, separate facts from assumptions, quantify business impact, and recommend practical next steps with calm, credible language.", "maxTokens": 900, "temperature": 0.46, "topP": 0.9, "topK": 40, "minP": 0, "repetitionPenalty": 1.02, "presencePenalty": 0, "frequencyPenalty": 0.08 }, "messages": [ { "role": "user", "content": "You are the overnight operations chief for a specialty food company. Create an executive-ready incident brief from the raw notes below. Output exactly these sections with clear headings: Situation Summary, Confirmed Facts, Key Risks, Decision Options, Recommended Plan, Draft Slack Update. Keep it concise, practical, and action-oriented. Use bullet points where helpful.\n\nRaw notes:\n- 11:40 PM: Refrigeration alarm at Phoenix cross-dock.\n- Two trailers affected: T17 and T22.\n- T17 contains temperature-sensitive artisan dairy for 14 grocery stores in Arizona and Nevada. T22 contains shelf-stable dry goods plus a small pallet of chocolate that can deform in heat.\n- Facility supervisor says backup generator kicked in but only powers one cooling zone reliably.\n- Last recorded trailer temps at 11:52 PM: T17 at 46F and rising from normal 36F; T22 at 68F.\n- QA policy: dairy above 41F for more than 2 hours requires hold-and-review; above 45F for more than 1 hour likely unsellable.\n- Driver pool: one reefer-capable tractor available in 25 minutes, one standard tractor available now.\n- Nearby cold-storage partner can accept 10 pallets immediately, 20 more by 3:00 AM. T17 has 24 pallets. T22 has 18 pallets total; chocolate is 2 pallets.\n- Storm cell causing intermittent outages across west Phoenix. Utility ETA unknown.\n- Finance note: spoilage exposure for T17 estimated at $84,000 retail, $31,000 cost. Late delivery penalties for 14 stores could total $9,500 if missed by 7:00 AM.\n- Sales note: tomorrow morning is a regional holiday promotion; high customer traffic expected.\n- Warehouse labor tonight: 6 associates on site, 2 certified for cold-chain transfers.\n- One store group says they can accept split delivery as late as 10:00 AM if notified by 4:30 AM.\n- Comms issue: previous false alarm this month made leadership skeptical; avoid overstatement.\n- Ask: prepare something the VP of Ops can read in under 2 minutes and forward to CEO if needed." } ] } ``` **Response**: ```json { "taskType": "textInference", "taskUUID": "653b1cb1-58a7-4c5a-b3fd-a75a7345684c", "text": "The user wants me to create an executive-ready incident brief from raw notes about a refrigeration failure at a cross-dock facility. I need to follow the exact sections requested:\n\n1. Situation Summary\n2. Confirmed Facts\n3. Key Risks\n4. Decision Options\n5. Recommended Plan\n6. Draft Slack Update\n\nLet me synthesize the information:\n\n**Situation Summary**: Refrigeration failure at Phoenix cross-dock affecting two trailers - one with temperature-sensitive dairy (T17) and one with dry goods + chocolate (T22). Backup generator only powers one cooling zone. Temps rising.\n\n**Confirmed Facts**:\n- Alarm at 11:40 PM\n- T17: 24 pallets of artisan dairy, currently 46F and rising (was 36F)\n- T22: 18 pallets total (16 dry goods + 2 chocolate), currently 68F\n- Backup generator only powers one zone\n- One reefer tractor available in 25 min, one standard now\n- Cold storage partner: can take 10 pallets now, 20 more by 3 AM\n- Storm causing intermittent outages, utility ETA unknown\n- 6 warehouse associates on site, 2 certified for cold-chain transfers\n- One store group can accept split delivery until 10 AM if notified by 4:30 AM\n\n**Key Risks**:\n- T17 dairy: above 41F for >2 hours = hold-and-review; above 45F for >1 hour = likely unsellable\n- Current T17 temp is 46F and rising - already past danger thresholds\n- T22 chocolate can deform in heat (68F is problematic)\n- $84K retail / $31K cost spoilage exposure\n- $9,500 late delivery penalties if missed by 7 AM\n- Holiday promotion tomorrow - high customer traffic expected\n\n\n- Leadership skepticism due to false alarm earlier this month\n\nI'm facing a critical time constraint with the dairy. At 46F and climbing, I've already exceeded the safety threshold. The clock is ticking - I have roughly an hour before the product becomes unsellable. My immediate focus needs to be rapid cooling or immediate transfer to prevent significant financial loss. The limited cold storage capacity and available resources make this a complex logistical challenge.\n\nI'll leverage the reefer tractor to transfer the most temperature-sensitive dairy pallets, prioritizing the product closest to spoilage. By mobilizing the two cold-chain certified associates and coordinating with the nearby cold storage facility, I can maximize my chances of minimizing product loss. The key is acting decisively within the next 60 minutes.\n\nFor communication, I'll craft a precise Slack message that highlights the critical nature of the situation, outlines our immediate actions, and sets clear expectations for resolution.\n\n\n# Incident Brief: Phoenix Cross-Dock Refrigeration Failure\n\n**Time:** 11:40 PM | **Priority:** High | **Location:** Phoenix Cross-Dock\n\n---\n\n## Situation Summary\n\nRefrigeration failure at Phoenix cross-dock affecting two trailers. Backup generator is powering only one cooling zone. T17 (dairy, 24 pallets) temperature rising and already exceeds safety thresholds. T22 (dry goods + chocolate, 18 pallets) also elevated. Storm activity causing ongoing utility instability. Decision required within 60 minutes to prevent product loss.\n\n---\n\n## Confirmed Facts\n\n- **Alarm received:** 11:40 PM at Phoenix cross-dock\n- **Affected trailers:**\n - **T17:** 24 pallets artisan dairy for 14 AZ/NV grocery stores — current temp 46°F (was 36°F, rising)\n - **T22:** 18 pallets total (16 dry goods + 2 chocolate) — current temp 68°F\n- **Infrastructure:** Backup generator active but reliably powers only one cooling zone\n- **Resources on-site:** 6 warehouse associates; 2 cold-chain certified for transfers\n- **Equipment available:**\n - Reefer-capable tractor: ~25 min out\n - Standard tractor: available now\n- **External capacity:** Cold-storage partner can accept 10 pallets immediately, 20 more by 3:00 AM\n- **Store flexibility:** One store group will accept split delivery as late as 10:00 AM if notified by 4:30 AM\n- **Weather:** Storm cell causing intermittent outages across west Phoenix; utility ETA unknown\n\n---\n\n## Key Risks\n\n| Risk | Impact |\n|------", "seed": 32945, "cost": 0.00099, "finishReason": "length" } ``` --- ### Moonshot Boardroom Decision Memo (Text to Text) **Request**: ```json { "taskType": "textInference", "taskUUID": "e79d2a2b-71da-486f-a4b6-50dc865f5515", "model": "minimax:m2.5@0", "seed": 67959, "settings": { "maxTokens": 1400, "temperature": 0.54, "topP": 0.9, "systemPrompt": "You are a high-performance strategy and operations assistant for executives. Produce structured, accurate, decision-oriented writing. Prioritize trade-off clarity, concise synthesis, and actionability. Do not invent numbers; where needed, label assumptions explicitly." }, "messages": [ { "role": "user", "content": "You are supporting an executive operating review for a startup called Tideglass, which sells AI workflow software to logistics companies. Convert the discussion notes below into a decision memo for the CEO. The memo must include: 1) executive summary, 2) decision options, 3) recommendation, 4) rationale, 5) risks and mitigations, 6) 30-day action plan, 7) open questions. Keep it crisp, practical, and leadership-ready.\n\nDiscussion notes:\n- Current ARR is $8.4M, growing 11% QoQ, but enterprise pipeline slipped because procurement cycles lengthened from 62 days to 96 days.\n- Mid-market segment is healthier: faster close times, lower ACV, better product adoption, but support load is high.\n- Sales wants to hire 4 more enterprise AEs now to chase a possible expansion with two national carriers. CRO says waiting could cause us to miss the buying window.\n- Finance says burn is already elevated after the platform migration; runway is 15 months if we keep current hiring plan, 12 months if we add the proposed AEs plus solutions engineers.\n- Product wants to delay the analytics module launch by 6 weeks to stabilize the new orchestration engine. CTO argues reliability is the key reason churn has improved.\n- CEO asked whether to prioritize near-term revenue or product trust. No consensus.\n- Customer success reports NRR is 118% overall, but 126% in customers using automation templates, only 101% in customers relying on custom implementations.\n- Operations lead says custom implementations are slowing onboarding and creating margin drag.\n- One strategic prospect wants an on-prem deployment; security team says that would require a separate compliance track and likely distract engineering for at least a quarter.\n- Marketing proposes an industry-specific campaign for cold-chain logistics, based on 3 recent wins and strong referenceability.\n- Head of partnerships says two channel partners could open mid-market distribution if packaging is simplified.\n- Board expectation from last meeting: show a credible path to efficient growth, not just top-line acceleration.\n- CEO preferences: hates vague memos, wants explicit trade-offs, owner names, and what not to do.\n\nAdditional instructions:\n- Assume today's date is May 14.\n- Use plain English, no buzzwords.\n- If data is incomplete, state assumptions clearly.\n- End with a short section titled 'What we are not doing.'" } ] } ``` **Response**: ```json { "taskType": "textInference", "taskUUID": "e79d2a2b-71da-486f-a4b6-50dc865f5515", "text": "Let me analyze this request carefully. I need to convert the discussion notes into a decision memo for the CEO of Tideglass, an AI workflow software startup for logistics companies.\n\nKey data points from the notes:\n- Current ARR: $8.4M, growing 11% QoQ\n- Enterprise pipeline slipped: procurement cycles lengthened from 62 to 96 days\n- Mid-market segment: healthier, faster close times, lower ACV, better adoption, but high support load\n- Sales wants: 4 more enterprise AEs to chase expansion with two national carriers\n- CRO warning: waiting could miss buying window\n- Finance: burn elevated after platform migration; runway 15 months (current plan) vs 12 months (with proposed hires)\n- Product wants: delay analytics module launch by 6 weeks to stabilize orchestration engine\n- CTO: reliability is key reason churn improved\n- CEO question: prioritize near-term revenue or product trust - no consensus\n- NRR: 118% overall, 126% with automation templates, 101% with custom implementations\n- Custom implementations: slowing onboarding, creating margin drag\n- Strategic prospect: wants on-prem deployment\n- Security team: would require separate compliance track, distract engineering for at least a quarter\n- Marketing: proposes industry-specific campaign for cold-chain logistics (3 recent wins, strong referenceability)\n- Partnerships: two channel partners could open mid-market distribution if packaging simplified\n- Board expectation: credible path to efficient growth, not just top-line acceleration\n- CEO preferences: hates vague memos, wants explicit trade-offs, owner names, what not to do\n- Date: May 14\n\nNow I need to structure this as a decision memo with:\n1. Executive summary\n2. Decision options\n3. Recommendation\n4. Rationale\n5. Risks and mitigations\n6. 30-day action plan\n7. Open questions\n8. What we are not doing\n\nLet me think about the key decisions to present:\n\n\nThe core tension centers on three strategic choices: whether to expand the enterprise sales team now or preserve runway, how to balance product reliability investments against revenue-generating features, and whether to pursue the on-premise deployment opportunity. The data strongly suggests that automation templates drive significantly better NRR (126% vs 101%), mid-market shows healthier unit economics despite higher support costs, and the board prioritizes efficient growth over pure top-line expansion. This points toward a recommendation that prioritizes mid-market efficiency and product stability over aggressive enterprise hiring, while explicitly declining the on-premise request due to engineering distraction.\n\n\n# Decision Memo: Tideglass Strategic Priorities\n\n**To:** CEO\n**From:** Strategy & Operations\n**Date:** May 14\n**Subject:** Operating Review Decisions — Enterprise Expansion vs. Runway, Product Roadmap, and Strategic Trade-offs\n\n---\n\n## 1. Executive Summary\n\nTideglass faces a critical juncture: enterprise sales cycles have lengthened significantly, consuming more sales resources per deal while pipeline velocity has slowed. Mid-market shows healthier unit economics but is creating support strain. The core tension is between two competing imperatives — accelerating enterprise expansion with two national carriers (requiring 4 new AEs and solutions engineers) versus preserving 15-month runway amid elevated burn post-migration.\n\n**Three decisions require your approval:**\n\n1. Whether to authorize the enterprise hiring request or maintain current headcount\n2. Whether to delay the analytics module by 6 weeks for stability work\n3. Whether to pursue the on-premise deployment request from the strategic prospect\n\n**Bottom line:** We recommend a balanced approach — authorize 2 enterprise AEs (not 4), proceed with the analytics launch on current timeline, and decline the on-prem request. This protects runway while capturing the national carrier opportunity, and prioritizes product reliability over new features given the strong correlation between stability and NRR.\n\n---\n\n## 2. Decision Options\n\n### Decision 1: Enterprise Sales Headcount\n\n| Option | Description | Runway Impact |\n|--------|-------------|---------------|\n| **A: Approve full request** | Hire 4 enterprise AEs + 2 solutions engineers | 12 months |\n| **B: Approve partial (recommended)** | Hire 2 enterprise AEs + 1 solutions engineer | ~13.5 months |\n| **C: Maintain status quo** | No additional enterprise hires | 15 months |\n\n### Decision 2: Analytics Module Launch Timing\n\n| Option | Description | Trade-off |\n|--------|-------------|-----------|\n| **A: Delay 6 weeks** | Prioritize orchestration engine stability | Revenue pushback; protects churn gains |\n| **B: Proceed on schedule (recommended)** | Launch analytics as planned | Accepts some stability risk; captures revenue timing |\n\n### Decision 3: On-Premise Deployment Request\n\n| Option | Description | Trade-off |\n|--------|-------------|-----------|\n| **A: Pursue on-prem** | Dedicated engineering track for one prospect | Distracts engineering for 1 quarter; opens enterprise door |\n| **B: Decline (recommended)** | Offer cloud-only with enhanced security briefing | Preserves engineering focus; may lose this prospect |\n\n---\n\n## 3. Recommendation\n\n**We recommend Option B for all three decisions:**\n\n1. **Hire 2 enterprise AEs + 1 solutions engineer** — This gives us coverage for one national carrier while preserving 13.5-month runway. The second carrier can be pursued through the channel partnership strategy (see below) at lower cost.\n\n2. **Launch analytics on current timeline** — The 126% NRR in automation-template customers versus 101% in custom implementations tells us reliability matters. However, the analytics module is a distinct release; we can ship it on schedule while maintaining the orchestration stability work as a parallel track.\n\n3. **Decline the on-prem request** — The engineering distraction (1 quarter) and compliance track cost outweigh the revenue from a single prospect. We should offer a security review call and cloud-based alternatives.\n\n**Additional recommendations embedded in the 30-day plan:**\n\n- Launch cold-chain logistics marketing campaign (3 referenceable wins support this)\n- Simplify mid-market packaging for the two channel partners ready to distribute\n- Shift customer success resources toward automation templates to improve NRR across the install base\n\n---\n\n## 4. Rationale\n\n**Why partial enterprise hiring (2 AEs, not 4):**\n\nThe CRO's concern about missing a buying window is legitimate. However, the data does not support a full 4-AE bet:\n\n- Enterprise procurement cycles have stretched from 62 to 96 days — a 55% increase. Adding more AEs does not shorten customer procurement time.\n- Mid-market close times remain faster with better product adoption. The channel partnership route to the second national carrier (via the two ready partners) carries lower cost and lower risk than direct enterprise sales.\n- The board explicitly asked for \"", "seed": 67959, "cost": 0.00148, "finishReason": "length" } ``` --- ### Maritime Supply Chain Disruption Memo (Text to Text) **Request**: ```json { "taskType": "textInference", "taskUUID": "d2dd7872-80fa-4d9d-8c3c-55eec188d9f8", "model": "minimax:m2.5@0", "seed": 50049, "settings": { "maxTokens": 700, "temperature": 0.55, "topP": 0.9, "systemPrompt": "You are a precise enterprise operations assistant. Produce structured, decision-ready outputs that synthesize tradeoffs, preserve business context, and avoid fluff." }, "messages": [ { "role": "user", "content": "You are supporting the COO of a specialty food importer. Draft a decision-ready executive memo based on the scenario below. Keep it under 450 words and use these exact section headings: Situation, Immediate Risks, Options, Recommendation, Next 72 Hours, Communication Notes.\n\nScenario:\n- A container carrying high-margin olive oil, tinned fish, and seasonal preserves from Lisbon to Newark has been delayed 11 days due to a labor slowdown and port congestion.\n- 38% of the shipment is already pre-allocated to three regional grocery chains for a Mediterranean promotion beginning next Friday.\n- Current warehouse stock can cover only 52% of expected promo demand.\n- Air freight is possible for the olive oil only, but it would reduce margin on those units by 18%.\n- One domestic co-packer can relabel substitute olive oil within 5 days, but quality is slightly lower and packaging will differ.\n- Sales says the chains will tolerate partial substitutions if notified by Tuesday noon and given revised merchandising copy.\n- Finance wants any response to preserve at least 70% of projected campaign gross profit.\n- The brand team is worried that visible inconsistency across SKUs could hurt perception during the promotion.\n\nWhat I need from you:\n1. Compare at least three options, including doing nothing, partial air freight, and domestic substitution.\n2. Recommend one path with a brief rationale.\n3. Include a bulleted action plan for the next 72 hours.\n4. Add communication notes for retail partners that are transparent but confidence-preserving.\n5. Be specific and practical, not generic." } ] } ``` **Response**: ```json { "taskType": "textInference", "taskUUID": "d2dd7872-80fa-4d9d-8c3c-55eec188d9f8", "text": "The user wants a decision-ready executive memo for a COO of a specialty food importer. Let me analyze the scenario:\n\n**Situation:**\n- Container delayed 11 days (Lisbon to Newark) due to labor slowdown/port congestion\n- 38% pre-allocated to 3 regional grocery chains for Mediterranean promotion starting next Friday\n- Current warehouse stock = 52% of expected promo demand\n- Promotion begins next Friday (5 days from now? Need to calculate)\n\n**Options:**\n1. Do nothing - wait for container\n2. Partial air freight for olive oil only (reduces margin by 18%)\n3. Domestic co-packer substitution (lower quality, different packaging)\n4. Hybrid approach - combine options\n\n**Constraints:**\n- Sales: chains tolerate partial substitutions if notified by Tuesday noon with revised merchandising copy\n- Finance: preserve at least 70% of projected campaign gross profit\n- Brand team: worried about perception if inconsistent across SKUs\n\nLet me think through the options:\n\n**Option 1: Do Nothing**\n- Wait for container arrival\n- Risk: May not arrive in time for Friday promo\n- Even if it arrives, only 52% stock available\n- This seems unacceptable given pre-commitments\n\n**Option 2: Partial Air Freight (olive oil only)**\n- Covers olive oil portion\n- Margin reduced by 18% on those units\n- Doesn't address tinned fish or preserves\n- Still leaves gap for other SKUs\n\n**Option 3: Domestic Substitution (olive oil via co-packer)**\n- 5 days to deliver\n- Lower quality, different packaging\n- Brand perception risk\n- But covers the gap\n\n**Option 4: Hybrid - Air freight olive oil + domestic substitution for olive oil + communicate substitution for other items**\n- This seems most viable\n\nLet me calculate:\n- 38% pre-allocated = significant commitment\n\n\n- Current stock = 52% of demand\n- Gap = 48% of demand unfilled\n\nThe core problem is that 48% of inventory is missing. I need to weigh the tradeoffs: air freight preserves margin but only covers olive oil, domestic substitution fills the gap but damages brand perception and quality, and doing nothing means missing the promotion entirely. The hybrid approach—air freighting olive oil while using domestic substitution for the remainder—seems like the only way to fulfill commitments while managing the brand risk.\n\nBut there's a timing issue. The container arrives 11 days late, and the promotion starts Friday. That's roughly 5 days away. Even with air freight, I'm cutting it extremely close on logistics. I should map out a 72-hour action plan: today I need to confirm which SKUs can be air-freighted and get the domestic co-packer lined up, tomorrow I place both orders and notify the retail chains, and by day three I'm executing on delivery and in-store setup.\n\nThe key constraint is the Tuesday noon deadline for substitutions—that gives me 48 hours from now to make the call. I also need to verify that air freight actually gets product to the East Coast by Thursday at the latest, otherwise the whole thing falls apart. The margin math matters too: if air freight cuts 18% off the top, I need to know whether that still leaves me above the 70% threshold Finance requires. The container's delayed 11 days, so even with expedited processing, it won't make the Friday promo. That's the core problem.\n\n", "seed": 50049, "cost": 0.00076, "finishReason": "length" } ``` --- ### Moonshot Launch Strategy Memo (Text to Text) **Request**: ```json { "taskType": "textInference", "taskUUID": "420d2b68-7fba-4580-a11b-107dd5ba7e60", "model": "minimax:m2.5@0", "seed": 99068, "settings": { "systemPrompt": "You are a precise enterprise strategy assistant. Synthesize ambiguous inputs into structured, decision-oriented deliverables. Prioritize clarity, tradeoff analysis, operational realism, and executive usefulness. Avoid fluff. Do not ask follow-up questions; make reasonable assumptions and state them briefly when needed.", "maxTokens": 1200, "temperature": 0.42, "topP": 0.9, "repetitionPenalty": 1.02 }, "messages": [ { "role": "user", "content": "You are acting as a senior chief-of-staff helping a startup CEO prepare for a board meeting. We are launching a new AI feature called 'Compass' for mid-market logistics companies. I need a board-ready strategy memo based on the messy notes below.\n\nContext:\n- Compass predicts shipment delays and suggests rerouting options.\n- Current customers love visibility, but operations teams dislike noisy alerts.\n- Sales wants broad launch in 6 weeks to support pipeline.\n- Product says the alert-threshold tuning UX is still confusing.\n- Legal says we must avoid any wording that implies guaranteed outcomes.\n- Finance wants gross margin above 68% by Q4.\n- Infra team says current model inference costs are 22% higher than target.\n- Customer Success reports best early adoption among accounts with 3+ distribution centers.\n- One major lighthouse customer is willing to co-market if we give them roadmap influence.\n- Security review is complete, but enterprise procurement questionnaires are slowing deals.\n- CEO priority order: credibility > growth > speed.\n\nPlease produce:\n1. An executive summary.\n2. A recommendation on whether to do a broad launch, limited launch, or delay.\n3. Top 5 risks with mitigation.\n4. A phased 90-day plan with owners.\n5. A short board-facing narrative on why this approach balances revenue, trust, and operational readiness.\n\nRequirements:\n- Be decisive, not generic.\n- Explicitly mention tradeoffs.\n- Use clear headers and bullet points.\n- Keep it concise but substantive.\n- Assume the audience is pragmatic and financially literate." } ] } ``` **Response**: ```json { "taskType": "textInference", "taskUUID": "420d2b68-7fba-4580-a11b-107dd5ba7e60", "text": "This is a comprehensive request for a board-ready strategy memo for a startup launching an AI feature called \"Compass\" for mid-market logistics companies. Let me analyze all the inputs and synthesize them into a clear, actionable document.\n\nKey data points from the context:\n1. Product: Compass - predicts shipment delays and suggests rerouting\n2. Customer feedback: Love visibility, but hate noisy alerts\n3. Sales: Wants broad launch in 6 weeks for pipeline support\n4. Product: Alert-threshold tuning UX is confusing\n5. Legal: Must avoid guaranteed outcome language\n6. Finance: Wants gross margin above 68% by Q4\n7. Infra: Model inference costs 22% above target\n8. Customer Success: Best adoption with 3+ distribution centers\n9. Lighthouse customer: Willing to co-market with roadmap influence\n10. Security: Review complete, but enterprise procurement questionnaires slowing deals\n11. CEO priority: credibility > growth > speed\n\nCEO priority order is critical here: credibility > growth > speed. This means I should NOT recommend a broad launch in 6 weeks given all the operational and product issues.\n\nLet me structure the memo:\n\n1. Executive Summary\n- Brief overview of Compass, the strategic situation, and the recommendation\n\n2. Recommendation (Launch Decision)\n- Given CEO priorities (credibility > growth > speed), I need to recommend a LIMITED LAUNCH\n- This balances the need to show progress (satisfying sales) while not launching with known product issues that would damage credibility\n- The lighthouse customer with co-marketing interest provides a perfect vehicle for a controlled launch\n\n3. Top 5 Risks with Mitigations\n- Need to identify the most critical risks and concrete mitigations\n- Should include: product quality/UX issues, margin/cost issues, legal/liability, sales pressure vs. product readiness, procurement delays\n\n4. Phased 90-Day Plan with Owners\n- Need clear phases with specific owners\n- Should address: fixing the UX, reducing inference costs, building the lighthouse relationship, preparing for broader launch\n\n\n- I'll craft a compelling narrative that emphasizes a deliberate, controlled approach to launching Compass\n- The story will highlight how a limited launch protects the company's reputation while setting the stage for sustainable growth\n- I'll focus on strategic patience, using the lighthouse customer as a proof point, and methodically addressing operational challenges before scaling\n\n\n# Board Strategy Memo: Compass Launch Decision\n\n**Prepared for:** Board of Directors\n**Date:** [Current Quarter]\n**Confidential**\n\n---\n\n## 1. Executive Summary\n\n**Recommendation: Limited Launch with 90-Day Hardening Phase**\n\nWe recommend a **controlled launch** targeting 8-12 accounts (focused on the 3+ DC segment) rather than broad availability in 6 weeks. This approach directly serves the CEO's stated priority order: **credibility > growth > speed**.\n\n**Why not broad launch in 6 weeks:**\n\n- Alert-UX is confusing—launching now risks eroding trust with early adopters\n- Inference costs are 22% above target—margins will miss the 68% Q4 target if uncorrected\n- Enterprise procurement questionnaires are already slowing deals—launching before resolving known issues compounds risk\n\n**Why not delay entirely:**\n\n- Sales pipeline pressure is real; we need to demonstrate market traction\n- Lighthouse customer is willing to co-market—too valuable to lose\n- Competitors are actively pursuing this segment\n\n**The limited launch strategy** lets us validate product-market fit with high-signal customers, fix the alert-UX and cost issues in production, and build referenceability before scaling. We project broad launch readiness by end of Q3, preserving Q4 margin targets.\n\n---\n\n## 2. Launch Decision: Limited Launch\n\n| Option | Credibility | Growth | Speed | Verdict |\n|--------|-------------|--------|-------|---------|\n| Broad launch in 6 weeks | ⚠️ High risk | High | Fast | **Reject** – product issues damage trust |\n| Limited launch (8-12 accounts) | ✅ Controlled | Moderate | Moderate | **Recommended** |\n| Delay to Q4 | ✅ High | Low | Slow | Reject – loses lighthouse, signals weakness |\n\n**Key Assumptions:**\n\n- Lighthouse customer (3+ DCs, willing to co-market) remains committed through Q2\n- Infra team can reduce inference costs by 15%+ within 60 days\n- Product team can ship UX improvements in 45 days\n\n---\n\n## 3. Top 5 Risks with Mitigations\n\n| # | Risk | Likelihood | Impact | Mitigation |\n|---|------|------------|--------|------------|\n| 1 | **Noisy alerts damage user trust** | High | Critical | Prioritize alert-threshold UX fix in first 30 days; implement user feedback loop before broad launch |\n| 2 | **Gross margin misses 68% target** | High | High | Reduce inference costs 15-20% via model optimization and batching; accept 2-3 month revenue delay to protect unit economics |\n| 3 | **Legal liability from prediction failures** | Medium | Critical | Draft explicit disclaimers in UI and contracts; frame as \"insights\" not \"predictions\"; train sales on approved language |\n| 4 | **Lighthouse customer walks** | Low | High | Formalize co-marketing agreement with roadmap influence; assign dedicated CS resource; deliver first 2 feature requests within 60 days |\n| 5 | **Enterprise procurement bottlenecks** | High | Medium | Pre-fill standard security questionnaires; create \"Compass security brief\" one-pager; prioritize deals with simpler procurement cycles |\n\n---\n\n## 4. Phased 90-Day Plan\n\n### Phase 1: Stabilize (Days 1-30)\n\n| Owner | Deliverable |\n|-------|-------------|\n| Product | Ship simplified alert-threshold UI (reduce from 7 to ", "seed": 99068, "cost": 0.00124, "finishReason": "length", "usage": { "promptTokens": 381, "completionTokens": 1200, "totalTokens": 1581 } } ```