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AUTHOR

Paul Sawers

Freelance tech writer at Tessl, former TechCrunch senior writer covering startups and open source

LinkedInX (Twitter)Substack

Articles

Article

What GitHub learned when better tools made Copilot code review worse

GitHub's migration of Copilot code review to shared tools initially worsened performance. Rewriting instructions improved accuracy and reduced costs by 20%.

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Article

Not all model ‘upgrades’ are upgrades — Microsoft data shows cheaper can cost more

Microsoft data reveals that newer AI models with lower per-token costs can end up more expensive due to higher token consumption, challenging assumptions about upgrades.

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Article

How context travels in a multi-agent world

Explore how context is managed in multi-agent systems, focusing on Microsoft's use of the A2A protocol to maintain coherent communication across independent AI agents.

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News

Cursor's new leaderboard shows teams the most popular plugins, skills and MCPs

Cursor's new leaderboard helps teams track popular plugins, skills, and MCPs, offering insights into usage patterns and facilitating better tool management.

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Article

Why Warp is betting engineering leaders are done picking a favourite coding agent

CEO Zach Lloyd talks multi-harness orchestration, why the CFO is now in the room for AI tool discussions, and what governed autonomy actually looks like on a “factory floor.”

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News

The hidden cost of agentic software development: why context engineering matters

AI token costs in software development are rising, impacting budgets. Context engineering is crucial for managing these expenses and ensuring efficient resource use.

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News

Anthropic details how attackers are weaponising Claude Code — but says AI will ultimately give defenders the edge

Anthropic's report reveals how attackers weaponize Claude Code for autonomous cyber attacks, but suggests AI advancements will eventually favor defenders.

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News

The model's solved, now comes the hard part: Reviewability as the bottleneck

AI engineering shifts focus from model development to ensuring system reviewability, emphasizing manageable task sizes for reliable and governable outputs.

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News

OpenAI is shutting down self-serve fine-tuning – what this signals for enterprise AI

OpenAI is phasing out self-serve fine-tuning, citing advanced models reducing its necessity, signaling a shift in enterprise AI towards infrastructure challenges.

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News

What 1,281 agent runs reveal about coding agent failure in large codebases

Sourcegraph's study of 1,281 agent runs in large codebases identifies infrastructure, not model capability, as the main bottleneck, revealing five common failure patterns.

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News

How enterprises are scaling AI: 5 patterns from OpenAI

OpenAI identifies five patterns for scaling AI in enterprises, focusing on operational integration, governance, and engineering ownership over model capabilities.

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News

Why multi-agent AI breaks in production — and how Yugabyte's Meko is trying to fix it

Yugabyte's Meko addresses multi-agent AI production issues by providing a shared memory and coordination layer, tackling state synchronization challenges in complex workflows.

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