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One thread, 3 models
Turn 1 GPT-6 Astra → drafts the clause → answer stored in shared memory
Turn 2 Claude Fable 5.1 → reads turn 1 from memory → argues the other side
Turn 3 Gemini 3.8 Flash → reads turns 1 and 2 → summarises both cheaply
You Nothing → no pasting, no re-briefing, no second tab
Every model reads the same thread. None of them stores it.
EducationalSeptember 14, 202610 min read

Switch AI Models Mid Conversation, Keep Context

Switch AI models mid conversation without repeating yourself. Shared memory holds context outside the model, which no single vendor subscription can offer.

switch-ai-models-mid-conversationshared-ai-memorymulti-model-ai
Same sticker, different bill Two models at $10 and $50. The gap lives in the cache column.
GPT-6 Astra Dearer cache, doubles on long prompts
  • Input $10, output $50 per 1M
  • Cache read $1 per 1M
  • Long prompts: $20 input, $75 output
  • Cache write $12.50 per 1M
Claude Fable 5.1 Cheaper cache, one flat tier
  • Input $10, output $50 per 1M
  • Cache read $0.25 per 1M
  • No long context surcharge
  • Cache write $12.50 per 1M
Compiled by ChatFuse from the OpenAI and Anthropic pricing pages, September 2026.
EducationalSeptember 8, 202612 min read

AI API Pricing Comparison: The 2026 Cost Guide

AI API pricing comparison for 2026: GPT-6 Astra, Claude Fable 5.1, Gemini 3.8 Flash and Meta Muse Spark, and why the sticker price is not the bill.

ai-api-pricing-comparisonllm-pricingai-model-cost
Two kinds of retirement The same word, two very different events.
When a person retires Handover is the default
  • Months of notice, often negotiated
  • They document what they know
  • They train a replacement
  • You can call them afterwards
When a model retires Handover does not exist
  • Notice is set by the provider
  • Nothing it learned is written down
  • The replacement starts at zero
  • Requests to it simply fail
Your prompts become a job description written for someone who no longer works there.
EducationalAugust 21, 202611 min read

AI Model Deprecation: Retirement With No Handover

AI model deprecation works like an employee retiring, except nothing gets handed over. Three providers, three notice periods, and what your business loses.

ai-model-deprecationmodel-retirementai-model-lifecycle
B2BAugust 16, 20268 min read

A Three Week AI Deployment, Told Week by Week

A three week AI deployment is realistic because the models already exist. The work is access, boundaries and a definition of done. Here is what each week holds.

three-week-ai-deploymententerprise-aiai-implementation
EducationalAugust 12, 202617 min read

The AI Org Chart: How to Run AI Like a Company

An AI org chart gives every AI role one clear job and one clear handoff. Here are the 25 roles we run our company on, and how to start with just 2.

ai-org-chartai-team-structureai-employees
B2BAugust 4, 20268 min read

Own Your AI Context, Rent the Models Above It

Own your AI context and rent the models. One layer of an AI system compounds in value, the other depreciates on somebody else's schedule. Know which is which.

own-your-ai-contextai-strategyvendor-lock-in
Build in publicJuly 28, 20268 min read

Multi Agent QA: Three Roles, One Document

Multi agent QA splits finding bugs from fixing them, because an agent that implements its own findings rationalises them. Here is the workflow we run.

multi-agent-qaai-agent-testingqa-workflow
EducationalJuly 20, 20268 min read

Self Maintaining AI Memory: Capture on a Timer

Self maintaining AI memory reads yesterday's transcripts on a schedule and updates itself. No human curation, and no hook interrupting you mid sentence.

self-maintaining-ai-memoryai-agent-memoryagent-state
EducationalJuly 13, 20268 min read

Rate Limiting Without Storing Who You Are

API rate limiting usually stores a user ID or IP as the key. Here is how ChatFuse throttles abuse without any identifier ever reaching the limiter.

api-rate-limitingabuse-preventiondata-minimization
EducationalJuly 5, 20268 min read

Cross Model Code Review: Test Your AI Reviewer

Cross model code review has one AI check another one's code. The part everyone skips is proving the reviewer is awake before trusting a clean result.

cross-model-code-reviewai-code-reviewai-coding-agents
Build in publicJune 28, 20269 min read

AI Agent Write Actions: The Confirmation Gate

AI agent write actions are the moment an assistant stops reading and starts doing. Here is the confirmation boundary we built so a model cannot send on its own.

ai-agent-write-actionsai-app-integrationsprompt-injection
EducationalJune 20, 20268 min read

Multi Model Agent Team: Three Jobs, Three Models

A multi model agent team gives each model one job it cannot mark its own work on. Opus orchestrates, Kimi finds, Sol implements. 181 findings in one day.

multi-model-agent-teamai-agent-orchestrationkimi-k3
EducationalJune 13, 202613 min read

Fable 5 vs GPT-5.6 Sol: No Single Winner

Fable 5 vs GPT-5.6 Sol: Fable wins on judgment and deep engineering, Sol on cost and agentic coding. Here is which model to use for which job, and why.

fable-5gpt-5-6-solai-model-comparison
EducationalJune 5, 20269 min read

AI Agent Skills: The Unit That Replaced Prompts

AI agent skills turn a prompt you retype into a versioned capability you can review and test. Here are the 27 we run, and the one that failed silently.

ai-agent-skillsagent-architectureprompt-engineering
EducationalMay 29, 20268 min read

How Energy Efficient AI Model Routing Works

Energy efficient AI model routing sends each prompt to the smallest model that can answer it, cutting energy per query 60% to 85% with the same output.

energy-efficient-aiai-model-routingsustainable-ai

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