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AI Agents

Orchestrator-Worker Patterns for Agents That Hold Up

The orchestrator-worker shape is the one multi-agent design that reliably pays for itself. Here is how to build the lead, the brief and the synthesis step.

· 9 min read
AI Agents

Parallel Tool Calls: When Concurrency Helps an Agent

Running tool calls concurrently cuts wall-clock time but not tokens, and it is only safe for some operations. How to decide what to parallelise.

· 8 min read
AI Agents

Partial Failure Recovery: When Half the Agents Succeed

Six workers, four returned, two timed out. Whether to answer, retry or abort is a design decision — here is how to make it before the incident, not during.

· 9 min read
AI Agents

Prompt Regression Testing: A CI Gate for Fuzzy Output

Prompt edits regress silently and every score is noisy. How to build a golden set, pick a scorer, handle variance and gate merges without a permanently red build.

· 9 min read
AI Agents

Rate Limiting Agent Fleets Without Killing Throughput

One API key, many agents, one shared quota. How to build a fleet-wide limiter that respects token budgets, protects interactive work and survives bursts.

· 9 min read
AI Agents

Replaying Agent Traces: Debugging a Run You Cannot Reproduce

Agent runs rarely reproduce, so the stored trace is the only evidence. What to capture, how to replay it, and where replay stops being faithful.

· 9 min read
AI Agents

Rollback Strategies for Agents That Changed Things

An agent stopped halfway through eleven changes. Checkpoints, compensating actions, staging areas and the undo plan you should require before it acts.

· 9 min read
AI Agents

Scratchpad Patterns: Giving an Agent Somewhere to Think

A durable scratchpad survives compaction, crashes and handoffs. What belongs on it, what does not, and how to stop it becoming a second transcript.

· 8 min read
AI Agents

Shared Memory Between Agents: Designs That Actually Hold

Agents that share a scratchpad drift, overwrite and confuse each other. Here are four shared-memory designs, what each one breaks, and how to pick.

· 9 min read
AI Agents

Speculative Agent Execution: Running Ahead of the Decision

Agents spend most of their wall-clock time waiting. Speculative execution starts likely next steps early and discards the wrong guesses. Here is when it pays.

· 9 min read
AI Agents

Summarisation in Agent Loops: Compressing Without Forgetting

Long sessions have to shed context. What to summarise, what must survive untouched, when to trigger it, and how to tell a good summary from a lossy one.

· 8 min read
AI Agents

The MCP Security Model: Trust Boundaries You Actually Have

MCP standardises connection, not trust. Here are the real boundaries in an MCP deployment and the attacks that cross them, with practical mitigations.

· 9 min read

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