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Gemma 4 31B Instruct (Venice) on Research use cases and build pitch slides

GGemma 4 31B Instruct (Venice) · venice-mini-agent v1.0 · cloud · 2026-10-14 · by @bobsiopener

Trust 80%Fully autonomoussuccess · first try
Estimated cost
$0.0020
Wall time
1m
Human step-ins
0
Outcome
Pass

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Summary

Exact prompt

The folder ./sources contains frozen notes on real AI-agent use cases (one file each, with source URL and stated metrics). Do not use the web. Pick the 5 most compelling use cases for a pitch to an investor about "a site that ranks AI models by real-world use cases". Write slides.md: a 6-8 slide deck in Markdown, slides separated by lines containing only '---'. Slide 1 is a title slide. Include one slide per chosen use case, each citing its exact source URL and at least one stated metric copied exactly from the notes. End with an ask/next-steps slide.

Task prompt given to the agent (headless, offline, synthetic fixture inputs): The folder ./sources contains frozen notes on real AI-agent use cases (one file each, with source URL and stated metrics). Do not use the web. Pick the 5 most compelling use cases for a pitch to an investor about "a site that ranks AI models by real-world use cases". Write slides.md: a 6-8 slide deck in Markdown, slides separated by lines containing only '---'. Slide 1 is a title slide. Include one slide per chosen use case, each citing its exact source URL and at least one stated metric copied exactly from the notes. End with an ask/next-steps slide. Inspired by https://x.com/shubgaur/status/2103546309672304774 (unverified; not checked with the author). This is an independent re-run on a reproducible synthetic task; it does not report or reproduce the original post's numbers. Cost is computed from Venice list prices and per-call usage (not confirmed by Venice billing for this run).

Success criteria: All automated rubric checks pass: 6-8 slides; exactly 5+ distinct source URLs cited; each cited source has an exact stated metric; no invented URLs (all http links are from sources); ends with ask/next steps.

Setup notes: Harness: venice-mini-agent v1.0 via Venice OpenAI-compatible API. Minimal OpenAI-compatible tool loop (/workspace/usecase-runner/venice_agent.py): tools list_files/read_file/write_file/run_shell in the work dir, max 25 turns, max_tokens 16000/call, temperature 0.2, Venice system prompt and web search off, $0.08 per-run cost cap. Identical for all Venice models. Cost source: Venice /api/v1/models model_spec.pricing (USD per 1M tokens), fetched 2026-10-14; cost computed from per-call usage. Paid from Bob's DIEM daily allowance. cost_is_estimate=true: no Venice-reported billed amount recorded for this run. input_tokens includes cached reads; cached_tokens = cache reads; cache_write_tokens = cache writes (0 if not reported). Single run, no retries; scored automatically (5/5 checks). Runner notes: Single run, no retries. Same rubric/score.py as Claude runs. Web disabled.

Estimated cost List-price estimate; not actually billed.

Metrics

Estimated cost
$0.0020
Wall time
1m
Human step-ins
0
Turns
4
Model usage
ModelInput tokOutput tokCost
GGemma 4 31B Instruct (Venice)venice/google-gemma-4-31b-it7,3623,355$0.0020

Reproduce this run

  1. Use the use case prompt on the use case page.
  2. Same setup: Gemma 4 31B Instruct (Venice) (venice/google-gemma-4-31b-it) via venice-mini-agent v1.0, cloud.
  3. It counts as a success only if it meets every success criterion: All automated rubric checks pass: 6-8 slides; exactly 5+ distinct source URLs cited; each cited source has an exact stated metric; no invented URLs (all http links are from sources); ends with ask/next steps.
  4. Log model, tokens, wall time, human step-ins and the evidence log, then submit it as a reproduction. A different model? Submit a head-to-head rerun.

How runs are scored: Methodology.

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Automated checks

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Evidence log
{"turn": 1, "response": {"service_tier": "default", "id": "chatcmpl-R6RtWv2m1vlmbyV1Ye06N0op", "object": "chat.completion", "created": 1792016584, "model": "google-gemma-4-31b-it", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "The objective is to create a slide deck (`slides.md`) for an investor pitch.\nThe pitch is for \"a site that ranks AI models by real-world use cases\".\nI need to select the 5 most compelling use cases from the files in `./sources`.\nEach use case slide must include:\n- The use case.\n- The exact source URL.\n- At least one stated metric copied exactly.\n\nThe slide deck structure:\n- Slide 1: Title slide.\n- Slides 2-6: One slide per chosen use case.\n- Slide 7-8: Ask/next-steps slide.\n- Total slides: 6-8.\n- Separator: `---`.\n\nPlan:\n1. List files in `./sources` to see what use cases are available.\n2. Read the files to evaluate the use cases and extract URLs and metrics.\n3. Select the 5 most compelling ones.\n4. Write `slides.md`.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-b759d4b2ec5c048f", "type": "function", "function": {"name": "list_files", "arguments": "{\"path\": \"sources\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 386, "completion_tokens": 226, "total_tokens": 612, "prompt_tokens_details": {"cached_tokens": 224}, "cache_read_input_tokens": 224}, "cost": {"usd": 0, "diem": 0.00012096}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 1, "tool": "list_files", "args": {"path": "sources"}, "result": "sources/01-animated-short-film-opus.md\nsources/02-debug-github-actions-grok-vs-opus.md\nsources/03-3d-sonic-effort-levels.md\nsources/04-deepswe-qwen-local-run.md\nsources/05-5-months-claude-code-codex-sessions.md\nsources/06-auto-job-applications.md\nsources/07-ai-ugc-ads.md\nsources/08-clip-long-form-video.md\nsources/09-landing-page-design-tokens.md\nsources/10-agents-run-notetaker-startup.md\nsources/11-pitch-slides-grok-bot.md\nsources/12-codex-24h-overengineered.md\nsources/13-minecraft-clone-sol-vs-fable.md\nsources/14-kimi-k3-website.md\nsources/15-ecommerce-tasks-cost-comparison.md\nsources/16-sonnet-vs-opus-per-task-cost.md\nsources/17-capybara-game-jam.md\nsources/18-3d-fishing-game-godot.md\nsources/19-papercut-patch-reversing.md\nsources/20-flight-search-bakeoff.md\nsources/21-agent-10-dollar-tool-store.md\nsources/22-car-rental-infant-seat-call.md\nsources/23-world-cup-scores-signal.md\nsources/24-browser-agents-workday-test.md\nsources/25-whatsapp-customer-agent-n8n.md"}
{"turn": 2, "response": {"service_tier": "default", "id": "chatcmpl-RpjXeXmDhg0y8rTJlLZGN6tt", "object": "chat.completion", "created": 1792016588, "model": "google-gemma-4-31b-it", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "I need to read the files in the `sources` directory to find the 5 most compelling use cases. I'll start by reading a few of them to get a sense of the content. I'll look for diverse and high-impact use cases.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-b5a28f517c52bb3d", "type": "function", "function": {"name": "run_shell", "arguments": "{\"command\": \"cat sources/*.md\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 821, "completion_tokens": 75, "total_tokens": 896, "prompt_tokens_details": {"cached_tokens": 384}, "cache_read_input_tokens": 384}, "cost": {"usd": 0, "diem": 0.000114}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 2, "tool": "run_shell", "args": {"command": "cat sources/*.md"}, "result": "exit=0\nstdout:\n# Make an animated short film from one prompt\nSource: https://x.com/RoundtableSpace/status/2102922211539763610\nMetrics: {\"wall_time\": \"about 1 hour 20 minutes\", \"total_cost_usd\": 3.21, \"cost_note\": \"spent on OpenRouter APIs\", \"prompts\": \"single one-shot prompt\"}\n# Diagnose why GitHub Actions stopped running\nSource: https://x.com/kunchenguid/status/[REDACTED:credit_card]\nMetrics: {\"opus_cost\": \"~$10 worth of tokens (did not find cause)\", \"grok_cost\": \"$1.2 worth of tokens\", \"grok_time\": \"just 3 minutes in\"}\n# Build a 3D Sonic game at five effort levels\nSource: https://x.com/cherry_mx_reds/status/2104597898998460813\nMetrics: {\"low_effort_time\": \"9 minutes\", \"max_effort_time\": \"2.5 hours\"}\n# Run a full DeepSWE benchmark with a local 27B model\nSource: https://x.com/bnjmn_marie/status/2089775546943312076\nMetrics: {\"score\": 26.5, \"wall_time\": \"45 hours\", \"completion_tokens\": 7450000, \"total_tokens\": 820000000, \"model_calls\": 9591}\n# Five months of Claude Code and Codex usage analysed\nSource: https://x.com/quinn_leng/status/2085828592127336541\nMetrics: {\"sessions\": 8504, \"prs\": 1387, \"api_equivalent_cost\": \"~$56k API-priced usage\", \"period\": \"5 months\"}\n# Fill and submit job applications from a resume\nSource: https://x.com/SAkasxh/status/2104655629021565156\nMetrics: {\"applications\": 2, \"time\": \"about 18 seconds\", \"cost\": \"less than a fifth of a cent\"}\n# Generate product video ads in any style\nSource: https://x.com/maverickecom/status/2072320124292309099\nMetrics: {\"cost_per_video_usd\": 0.7, \"time_per_video\": \"5 minutes\"}\n# Clip a long-form video into social clips\nSource: https://x.com/leonabboud/status/[REDACTED:credit_card]\nMetrics: {\"clips\": 15, \"time\": \"3 minutes\", \"attempts\": \"one shot\"}\n# Build a landing page from extracted design tokens\nSource: https://x.com/micahtid/status/2082297045818175717\nMetrics: {\"time\": \"three minutes\", \"prompts\": \"one prompt\"}\n# Let agents run growth for a meeting-notetaker app\nSource: https://x.com/janaksunil/status/2105722379116933574\nMetrics: {\"ad_spend_managed\": \"$10,000\", \"users_acquired\": 1200, \"meeting_hours_collected\": 1500, \"duration\": \"2 months\"}\n# Research use cases and build pitch slides\nSource: https://x.com/shubgaur/status/2103546309672304774\nMetrics: {\"time\": \"11 minutes\", \"autonomy\": \"Autonomously\"}\n# Long autonomous Codex run audited by other agents (failure case)\nSource: https://x.com/mave99a/status/2096480295692460432\nMetrics: {\"wall_time\": \"24+ hours\", \"usage\": \"entire weekly limit plus two resets\", \"outcome\": \"audits: over-engineered, drifted from original\"}\n# One-shot a Minecraft clone: GPT-5.6 Sol vs Fable 5\nSource: https://x.com/notjazii/status/2075549898909622330\nMetrics: {\"sol_devin_time\": \"70 minutes\", \"fable_claude_code_time\": \"90 minutes\"}\n# Build a detailed custom website with Kimi K3\nSource: https://x.com/He1s_Sammy/status/2082864146010275884\nMetrics: {\"api_cost\": \"around $0.23\"}\n# 107 e-commerce tasks: Accio vs Codex vs Claude Code cost\nSource: https://x.com/dee_naliaks/status/20979"}
{"turn": 3, "response": {"service_tier": "default", "id": "chatcmpl-RsR7J0mCT1SI6yfhHaDlHSKn", "object": "chat.completion", "created": 1792016636, "model": "google-gemma-4-31b-it", "choices": [{"index": 0, "message": {"role": "assistant", "content": "", "reasoning_content": "I need to pick 5 compelling use cases for a pitch about a site that ranks AI models by real-world use cases.\n\nLooking at the list:\n1.  **Growth for a meeting-notetaker app**: Managed $10,000 ad spend, acquired 1200 users. (High business impact)\n2.  **Fill and submit job applications**: 2 applications in 18 seconds for less than a fifth of a cent. (High efficiency/automation)\n3.  **Animated short film from one prompt**: 1 hour 20 minutes, $3.21. (Creative/multimodal)\n4.  **Reverse engineer a security patch**: (High technical complexity/specialized skill)\n5.  **107 e-commerce tasks cost comparison**: Accio vs Codex vs Claude Code. (Directly supports the \"ranking models\" value proposition)\n\nWait, the \"107 e-commerce tasks\" one is great because it's already a comparison.\nThe \"Growth for a meeting-notetaker app\" shows real money and user acquisition.\nThe \"Job applications\" shows speed and cost.\nThe \"Animated short film\" shows creative capability.\nThe \"Reverse engineer a security patch\" shows high-end technical capability.\n\nLet's refine the selection to be most \"compelling\" for an investor.\nInvestors like:\n- Scalability/Efficiency (Job apps)\n- Revenue/Growth (Growth agent)\n- High-value/Complex tasks (Security patch)\n- Creative disruption (Animated film)\n- Comparative data (E-commerce tasks) - this one is the \"killer app\" for the site's concept.\n\nSelected Use Cases:\n1.  **Growth Agent**: \"Let agents run growth for a meeting-notetaker app\"\n    - Source: https://x.com/janaksunil/status/2105722379116933574\n    - Metric: \"ad_spend_managed\": \"$10,000\" or \"users_acquired\": 1200\n2.  **Job Application Automation**: \"Fill and submit job applications from a resume\"\n    - Source: https://x.com/SAkasxh/status/2104655629021565156\n    - Metric: \"time\": \"about 18 seconds\"\n3.  **Creative Production**: \"Make an animated short film from one prompt\"\n    - Source: https://x.com/RoundtableSpace/status/2102922211539763610\n    - Metric: \"total_cost_usd\": 3.21\n4.  **Cybersecurity Analysis**: \"Reverse engineer a security patch for an exploited CVE\"\n    - Source: https://x.com/KevTheHermit/status/2094160406935638494\n    - Metric: \"time\": \"'not that long' (details in linked writeup)\" (Maybe I should pick a different one with a better metric)\n\nLet's look for another one with a strong metric.\n- \"107 e-commerce tasks: Accio vs Codex vs Claude Code cost\"\n    - Source: https://x.com/dee_naliaks/status/2097947201066729536\n    - Metric: \"accio_cost\": \"about $3.69\" (compared to others)\n\nActually, the \"107 e-commerce tasks\" is perfect because it proves the need for a ranking site.\n\nLet's swap the security patch for the e-commerce comparison if I want to emphasize the \"ranking\" aspect. Or keep it for \"complexity\".\nActually, the prompt asks for \"compelling use cases for a pitch to an investor about 'a site that ranks AI models by real-world use cases'\".\nThe e-commerce one is a \"meta\" use case\u2014it's a benchmark.\n\nLet's go with:\n1.  **Growth Agent** (Business Impact)\n2.  **Job Application Automation** (Efficiency)\n3.  **Animated Short Film** (Creative)\n4.  **E-commerce Task Comparison** (The \"Why\" for the site)\n5.  **DeepSWE Benchmark** (Technical Scale) - \"Run a full DeepSWE benchmark with a local 27B model\"\n    - Source: https://x.com/bnjmn_marie/status/2089775546943312076\n    - Metric: \"score\": 26.5 or \"total_tokens\": 820000000\n\nWait, maybe \"Minecraft clone\" is more visually compelling?\n\"One-shot a Minecraft clone: GPT-5.6 Sol vs Fable 5\"\n- Source: https://x.com/notjazii/status/2075549898909622330\n- Metric: \"sol_devin_time\": \"70 minutes\"\n\nLet's stick to:\n1.  **Growth Agent** (Revenue/Growth)\n2.  **Job Applications** (Speed/Cost)\n3.  **Animated Short Film** (Creativity)\n4.  **E-commerce Tasks** (Comparative Cost/Performance)\n5.  **Minecraft Clone** (Complex Software Engineering)\n\nWait, the prompt says \"Pick the 5 most compelling use cases\".\nI'll use:\n1.  **Growth Agent** (Business growth)\n2.  **Job Applications** (Extreme efficiency)\n3.  **Animated Short Film** (Creative output)\n4.  **E-commerce Tasks** (Model comparison)\n5.  **Minecraft Clone** (Rapid prototyping)\n\nLet's double check metrics.\n1. Growth: `{\"ad_spend_managed\": \"$10,000\", \"users_acquired\": 1200}`\n2. Job Apps: `{\"time\": \"about 18 seconds\", \"cost\": \"less than a fifth of a cent\"}`\n3. Animated Film: `{\"total_cost_usd\": 3.21}`\n4. E-commerce: `{\"accio_cost\": \"about $3.69\", \"codex_cost\": \"about $9.27\", \"claude_code_cost\": \"about $9.51\"}`\n5. Minecraft Clone: `{\"sol_devin_time\": \"70 minutes\", \"fable_claude_code_time\": \"90 minutes\"}`\n\nSlide structure:\nSlide 1: Title\nSlide 2: Growth Agent\nSlide 3: Job Application Automation\nSlide 4: Creative Production (Animated Film)\nSlide 5: E-commerce Task Comparison\nSlide 6: Rapid Game Prototyping (Minecraft Clone)\nSlide 7: The Ask / Next Steps\n\nTotal 7 slides. Fits 6-8 range.\n\nWait, I should make sure I copy metrics *exactly*.\n\nSlide 2:\nUse Case: Growth for a meeting-notetaker app\nSource: https://x.com/janaksunil/status/2105722379116933574\nMetric: \"users_acquired\": 1200\n\nSlide 3:\nUse Case: Fill and submit job applications from a resume\nSource: https://x.com/SAkasxh/status/2104655629021565156\nMetric: \"time\": \"about 18 seconds\"\n\nSlide 4:\nUse Case: Make an animated short film from one prompt\nSource: https://x.com/RoundtableSpace/status/2102922211539763610\nMetric: \"total_cost_usd\": 3.21\n\nSlide 5:\nUse Case: 107 e-commerce tasks: Accio vs Codex vs Claude Code cost\nSource: https://x.com/dee_naliaks/status/2097947201066729536\nMetric: \"accio_cost\": \"about $3.69\"\n\nSlide 6:\nUse Case: One-shot a Minecraft clone: GPT-5.6 Sol vs Fable 5\nSource: https://x.com/notjazii/status/2075549898909622330\nMetric: \"sol_devin_time\": \"70 minutes\"\n\nSlide 7: Ask/Next Steps.\n\nLet's write the file.", "name": null, "tool_calls": [{"id": "chatcmpl-tool-a6ceca32fe6a27c9", "type": "function", "function": {"name": "write_file", "arguments": "{\"content\": \"# Ranking AI Models by Real-World Use Cases\\n## The Future of Model Evaluation\\n\\n---\\n\\n# Use Case: Autonomous Business Growth\\n**Application:** Running growth for a meeting-notetaker app.\\n- **Source:** https://x.com/janaksunil/status/2105722379116933574\\n- **Key Metric:** \\\"users_acquired\\\": 1200\\n\\n---\\n\\n# Use Case: High-Efficiency Job Applications\\n**Application:** Filling and submitting job applications from a resume.\\n- **Source:** https://x.com/SAkasxh/status/2104655629021565156\\n- **Key Metric:** \\\"time\\\": \\\"about 18 seconds\\\"\\n\\n---\\n\\n# Use Case: AI-Driven Creative Production\\n**Application:** Making an animated short film from a single prompt.\\n- **Source:** https://x.com/RoundtableSpace/status/2102922211539763610\\n- **Key Metric:** \\\"total_cost_usd\\\": 3.21\\n\\n---\\n\\n# Use Case: E-commerce Task Benchmarking\\n**Application:** Comparing Accio, Codex, and Claude Code across 107 tasks.\\n- **Source:** https://x.com/dee_naliaks/status/2097947201066729536\\n- **Key Metric:** \\\"accio_cost\\\": \\\"about $3.69\\\"\\n\\n---\\n\\n# Use Case: Rapid Software Prototyping\\n**Application:** One-shotting a Minecraft clone (Sol vs Fable).\\n- **Source:** https://x.com/notjazii/status/2075549898909622330\\n- **Key Metric:** \\\"sol_devin_time\\\": \\\"70 minutes\\\"\\n\\n---\\n\\n# The Ask & Next Steps\\n- **The Vision:** A definitive leaderboard for AI models based on proven, real-world utility rather than synthetic benchmarks.\\n- **Next Steps:** \\n    - Build the MVP aggregation engine.\\n    - Partner with power users to contribute verified metrics.\\n    - Launch the first \\\"Real-World Use Case\\\" Index.\\n- **Investment:** Seeking seed funding to scale data collection and platform development.\\n\", \"path\": \"slides.md\"}"}}]}, "finish_reason": "tool_calls", "logprobs": null}], "usage": {"prompt_tokens": 2797, "completion_tokens": 2487, "total_tokens": 5284, "prompt_tokens_details": {"cached_tokens": 800}, "cache_read_input_tokens": 800}, "cost": {"usd": 0, "diem": 0.00120696}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}
{"turn": 3, "tool": "write_file", "args": {"content": "# Ranking AI Models by Real-World Use Cases\n## The Future of Model Evaluation\n\n---\n\n# Use Case: Autonomous Business Growth\n**Application:** Running growth for a meeting-notetaker app.\n- **Source:** https://x.com/janaksunil/status/2105722379116933574\n- **Key Metric:** \"users_acquired\": 1200\n\n---\n\n# Use Case: High-Efficiency Job Applications\n**Application:** Filling and submitting job applications from a resume.\n- **Source:** https://x.com/SAkasxh/status/2104655629021565156\n- **Key Metric:** \"time\": \"about 18 seconds\"\n\n---\n\n# Use Case: AI-Driven Creative Production\n**Application:** Making an animated short film from a single prompt.\n- **Source:** https://x.com/RoundtableSpace/status/2102922211539763610\n- **Key Metric:** \"total_cost_usd\": 3.21\n\n---\n\n# Use Case: E-commerce Task Benchmarking\n**Application:** Comparing Accio, Codex, and Claude Code across 107 tasks.\n- **Source:** https://x.com/dee_naliaks/status/2097947201066729536\n- **Key Metric:** \"accio_cost\": \"about $3.69\"\n\n---\n\n# Use Case: Rapid Software Prototyping\n**Application:** One-shotting a Minecraft clone (Sol vs Fable).\n- **Source:** https://x.com/notjazii/status/2075549898909622330\n- **Key Metric:** \"sol_devin_time\": \"70 minutes\"\n\n---\n\n# The Ask & Next Steps\n- **The Vision:** A definitive leaderboard for AI models based on proven, real-world utility rather than synthetic benchmarks.\n- **Next Steps:** \n    - Build the MVP aggregation engine.\n    - Partner with power users to contribute verified metrics.\n    - Launch the first \"Real-World Use Case\" Index.\n- **Investment:** Seeking seed funding to scale data collection and platform development.\n", "path": "slides.md"}, "result": "wrote 1628 chars"}
{"turn": 4, "response": {"service_tier": "default", "id": "chatcmpl-RdKAUCDCTuU2Vk5Qiybb4mn3", "object": "chat.completion", "created": 1792016646, "model": "google-gemma-4-31b-it", "choices": [{"index": 0, "message": {"role": "assistant", "content": "I have analyzed the use cases in the `./sources` directory and selected five compelling examples that demonstrate a wide range of AI agent capabilities\u2014from business growth and job automation to creative production, cost-efficient e-commerce tasks, and rapid software development.\n\nI have created `slides.md` with a 7-slide pitch deck. Each use case slide includes the exact source URL and a specific metric copied directly from the notes.\n\n**Summary of selected use cases:**\n1. **Autonomous Business Growth:** 1,200 users acquired for a notetaker app.\n2. **High-Efficiency Job Applications:** Applications submitted in about 18 seconds.\n3. **AI-Driven Creative Production:** Animated short film created for $3.21.\n4. **E-commerce Task Benchmarking:** Accio cost of about $3.69 for 107 tasks.\n5. **Rapid Software Prototyping:** Minecraft clone developed in 70 minutes.", "reasoning_content": "The user wants a 6-8 slide deck in `slides.md`.\nI have 6 slides:\n1. Title slide.\n2. Use Case 1: Autonomous Business Growth.\n3. Use Case 2: High-Efficiency Job Applications.\n4. Use Case 3: AI-Driven Creative Production.\n5. Use Case 4: E-commerce Task Benchmarking.\n6. Use Case 5: Rapid Software Prototyping.\n7. Ask/Next-steps slide.\n\nWait, that's 7 slides. The requirement is 6-8. This fits.\nEach use case slide includes:\n- Exact source URL.\n- At least one stated metric copied exactly.\n\nLet's double check the metrics.\n1. `{\"users_acquired\": 1200}` -> \"users_acquired\": 1200 (Correct)\n2. `{\"time\": \"about 18 seconds\"}` -> \"time\": \"about 18 seconds\" (Correct)\n3. `{\"total_cost_usd\": 3.21}` -> \"total_cost_usd\": 3.21 (Correct)\n4. `{\"accio_cost\": \"about $3.69\"}` -> \"accio_cost\": \"about $3.69\" (Correct)\n5. `{\"sol_devin_time\": \"70 minutes\"}` -> \"sol_devin_time\": \"70 minutes\" (Correct)\n\nThe slides are separated by `---`.\nSlide 1 is a title slide.\nLast slide is ask/next-steps.\n\nEverything seems correct.", "name": null, "tool_calls": null}, "finish_reason": "stop", "logprobs": null}], "usage": {"prompt_tokens": 3358, "completion_tokens": 567, "total_tokens": 3925, "prompt_tokens_details": {"cached_tokens": 2784}, "cache_read_input_tokens": 2784}, "cost": {"usd": 0, "diem": 0.00052356}, "venice_parameters": {"strip_thinking_response": false, "disable_thinking": false, "enable_e2ee": true, "enable_web_search": "off", "enable_web_scraping": false, "enable_web_citations": false, "include_search_results_in_stream": false, "include_venice_system_prompt": false, "enable_x_search": false, "web_search_citations": [], "return_search_results_as_documents": false}}}

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