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How to choose an agent harness for your workload

Your agent harness is an architectural decision that directly dictates task success and API costs. Here is how to match it to your workload.

Akruti Acharya·deep dive

KV cache techniques for faster, cheaper multi-model AI agents

Nvidia's Qwen3 14B to 32B mapper is 25.1x vs re-prefill at 32,768 tokens. Cache-to-Cache reports about 2.5x against text

Ben Dickson·deep dive

New AI Architecture Challenges Token-by-Token Generation

Rough concept first, then the words. 10x to 31x faster than strong diffusion models, on 4x to 5x fewer training tokens

Ben Dickson·deep dive

Prompt Injection is an Information-Flow Problem

How prompt injection exploits trust boundaries through saved memory, and what runtime checks can prevent unsafe actions.

Akruti Acharya·deep dive

Looped transformers: three different machines

Classify depth, time, or flow. Nanbeige is the downloadable LLM. RLT lost at 140M. Looped Flows is a 5-7M puzzle net

Adham Khaled·deep dive


How AI Agents Are Learning to Rewrite Their Own Stack

Self-Harness reports relative gains of up to 132%. EnvHarness adds up to 9.0 points and 9.8% fewer steps

Ben Dickson·deep dive

What Belongs in AGENTS.md, Design Docs and Tests?

Why agent instructions accumulate and how to decide what to keep, move, or remove.

Akruti Acharya·deep dive

System One models are carving out a new layer in the AI stack

TypeSafe's Jev returns a typed answer in 70 to 500 ms at $0.042 per million input tokens, with no metered output-token cost

Ben Dickson·deep dive

How to Review Your Vibe Coded App Before Deployment

METR’s API key theft shows why you must check authentication, credential access, and permissions before deployment.

Akruti Acharya·deep dive

development

Understanding the “Harness Tax” Behind Coding Agents

21 combos, 60 tasks, 5x cost swing, and a 4-tool harness on the Pareto frontier

Ben Dickson·Sep 21

llms

What DeepSeek-V4.1-Flash teaches us about efficient AI

A 552B model with 890-byte KV cache, 8B active on input, and an Artificial Analysis 40 versus Gemini 3.8 Flash High at 41

Ben Dickson·Sep 14

development

When to Gate Recursive Terminal-task Synthesis

Mark each agent job Promote, Hybrid, or Reject. RST is allowed only when the job is hermetic, bounded, reproducible, and outcome-verifiable

Adham Khaled·Sep 08

post training

What Developers Can Learn From Shopify’s Self-Improving AI Pipeline

Fine-tuned 0.8B Qwen beat GPT-5.6 Sol xhigh, 2 million buyer profiles a day became 72 million, and GraphQL serving fell from $27 million to $1 million

Ben Dickson·Sep 07

agents

Coding Agent Cost: Why Sessions Get Expensive

Keep the project on disk, treat lunch as a bill, and score the first finished tasks rather than dollars per million tokens

Adham Khaled·Sep 03

agents

Rebuilding the Runtime: What NVIDIA NOOA Reveals About Agent Frameworks

Its object-oriented model clarifies the trade-off between live program state and durable runtime control.

Akruti Acharya·Sep 02

security

What a Week of AI Security Incidents Means for Developers

Seven practical shifts for securing agents that can find any crack

Ben Dickson·Aug 31

security

Encrypted Reasoning Traces on Your Laptop: Resume or Strip

Public traces hid 315,320 encrypted blocks. Treat resume logs and publish logs as two paths, then count the field on your own machine.

Adham Khaled·Aug 25

agents

AI agent skills: Why they succeed and what causes them to crash

Everyone's adding skills to their agents. Almost no one knows when they help, why they work, or where they fail.

Ben Dickson·Aug 24

agents

Does Self-Improvement Still Work on an Engineered Agent Harness?

How self-improving agent harnesses can look better in validation than they perform on unseen tasks.

Akruti Acharya·Aug 19

agents

MCP Went Stateless: What Must Change on Your Servers

2026-07-28 drops protocol sessions. A local place_order went 1 to 2 orders unless I sent an order id.

Adham Khaled·Aug 18


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