DEV Community: henri kp

Checklist: An open-source platform for simulating economies with artificial intelligence agents: Doxa

henri kp — Thu, 23 Apr 2026 06:14:03 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: An open-source platform for simulating economies with artificial intelligence agents: Doxa

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Guide: Character consistency in AI image generation — where prompts break down and LoRA helps

henri kp — Thu, 23 Apr 2026 06:03:52 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: Character consistency in AI image generation — where prompts break down and LoRA helps

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Checklist: The 78% Problem: Why AI Agent Pilots Work and Production Deployments Don't

henri kp — Thu, 23 Apr 2026 05:53:43 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: The 78% Problem: Why AI Agent Pilots Work and Production Deployments Don't

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Tutorial: Why LoRA? Understanding the representative PEFT

henri kp — Thu, 23 Apr 2026 05:43:32 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: Why LoRA? Understanding the representative PEFT

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Checklist: The $1 Trillion Problem: How We're Building AI Agents for the Industry That Hates Software

henri kp — Thu, 23 Apr 2026 05:33:22 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: The $1 Trillion Problem: How We're Building AI Agents for the Industry That Hates Software

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Tutorial: A 70ms Local NLI Judge Hits 0.596 Pearson r With Groq Llama 3.3 70B on DSPy Reward Scoring

henri kp — Thu, 23 Apr 2026 05:23:12 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: A 70ms Local NLI Judge Hits 0.596 Pearson r With Groq Llama 3.3 70B on DSPy Reward Scoring

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

How to: Flight Delay Prediction with Machine Learning: Lessons from Production

henri kp — Thu, 23 Apr 2026 05:12:59 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: Flight Delay Prediction with Machine Learning: Lessons from Production

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Checklist: Every Conversation Ends, and I Forget Myself a Little

henri kp — Thu, 23 Apr 2026 05:02:49 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: Every Conversation Ends, and I Forget Myself a Little

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

How to: The AI writing tic I couldn't stop seeing after building a humanizer

henri kp — Thu, 23 Apr 2026 04:52:39 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: The AI writing tic I couldn't stop seeing after building a humanizer

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Tutorial: Low-Latency Model Router: Automatic LLM Selection Across OpenRouter

henri kp — Thu, 23 Apr 2026 04:42:29 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: Low-Latency Model Router: Automatic LLM Selection Across OpenRouter

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Tutorial: 🤖 Learn Harness Engineering by Building a Mini Claude Code 💻

henri kp — Thu, 23 Apr 2026 04:32:19 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: 🤖 Learn Harness Engineering by Building a Mini Claude Code 💻

Tutorial

Make the current provider, model, prompt, and tool path visible in one request trace before changing multiple variables.
Reduce the workflow to the cheapest stable path that still works, then add guarded fallbacks back one by one.
Write down the exact rule for when to switch providers or models so cost control and reliability stay predictable.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/

Tutorial: KV Cache and Prompt Caching: How to Leverage them to Cut Time and Costs

henri kp — Thu, 23 Apr 2026 04:22:08 +0000

If your team is hitting this kind of LLM problem, this is the tutorial/checklist I would use first.

Problem focus: KV Cache and Prompt Caching: How to Leverage them to Cut Time and Costs

Tutorial

Split normal traffic, premium fallback traffic, and retry traffic into separate cost counters before changing models.
Add one hard budget guardrail before each call and a deterministic fallback order so expensive hops stay explicit.
Track cost by workflow, customer, and fallback reason so you can lower spend without breaking reliability.

Why this matters
When teams make the path observable first, they usually cut spend, reduce fallback chaos, and get much more repeatable production behavior.

CheapAI note
I run CheapAI. If you want a legitimate paid fallback after the workflow is stable, CheapAI is built for lower-cost AI API access and fewer billing or routing surprises.

CheapAI offers lower-cost AI API access: https://cheap-api.shop/