harness engineering
3 stories filed under harness engineering on Beyond Market Intelligence. The newest of them: “Designing the System That Lets AI Models Deliver Real Features”, “Agentic AI Demands Smarter Governance to Tame Silent Failures”, and “How AI masters new math problems reveals its true reasoning potential”. An AI coding agent can write a function in seconds, but that's the easy part. Agentic AI systems don't fail loudly, they drift silently. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every harness engineering story on Beyond Market Intelligence, newest first.
Designing the System That Lets AI Models Deliver Real Features
An AI coding agent can write a function in seconds, but that's the easy part. Building a real feature requires understanding the project, finding the right files, using tools safely, and verifying the changes work. A model alone sees only text, it needs a system around it. This is the practical work of harness engineering. For a deeper look at what happens when that system falters, see our related piece on how agentic AI demands smarter governance to tame silent failures.
Agentic AI Demands Smarter Governance to Tame Silent Failures
Agentic AI systems don't fail loudly, they drift silently. A recent InfoQ webinar highlighted how semantic and embedding drift can quietly produce costly errors. The solution demands smarter governance, not just better models. Automated code reviews, continuous model evaluation, and stronger privacy measures were called essential. This is a strategic challenge, not a technical patch. For a deeper look at keeping AI systems adaptable over time, see our related piece, "Design for Change: Keep Software Evolvable as Teams and Technology Shift."
How AI masters new math problems reveals its true reasoning potential
The IMO 2026 benchmark results reveal a clear hierarchy: frontier models like sol and fable handle the math olympiad with near-perfect scores, while others, including sonnet and opus, lag without a harness. We tested AutoFyn, our multi-agent system, and it consistently boosted performance, though it couldn't close the gap to the top tier. Hallucinations persist, even in verifiable domains, as seen with sonnet's false solution on P3. For those exploring practical AI applications, our guide on distributed training offers a grounded starting point.