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37 articles tagged Agentic Coding.
An analysis of how agentic coding shifts software development from individual execution to collaborative planning. This brief explores the limitations of text-based interfaces, the role of visual boundary objects, and the strategic redefinition of PM and engineering roles in an AI-native workflow.
Dan Fu of Together AI discusses the convergence of academic research and production engineering. The analysis covers the shift toward inference-centric cloud infrastructure, the role of domain expertise in AI-assisted coding, and frameworks for managing agentic engineering teams.
Gregory Kurtzer outlines the OpenWaldo framework, arguing that true open source AI requires open weights, artifacts, licenses, data, and origins. The discussion highlights the critical role of AI Bills of Materials in mitigating enterprise risk and ensuring accountability in agentic workflows.
A strategic framework for securing autonomous AI agents in software factories. Learn how to implement sandboxing, least privilege, and supply chain controls to mitigate risks from probabilistic AI actors.
Rafi Ayoub, CTO of Mozilla, discusses the strategic shift toward open-source AI ecosystems, the obsolescence of traditional SDLCs in agentic coding, and the necessity for CTOs to maintain vendor leverage. The analysis covers the transition from subscription to token pricing, the rise of local inference, and the mission to democratize AI access beyond big tech monopolies.
This analysis explores the architecture of agentic software factories, focusing on the implementation of inner, middle, and outer feedback loops. It details how engineering teams can transition from manual prompting to autonomous, self-healing systems by treating code, context, and data as integral factory components.
Legora CTO Jacob Lauritsen details how AI writes 100% of their codebase and drives $200M ARR. Learn about agentic orchestration, the verifier rule, and why human judgment remains critical in high-stakes legal decisions.
Meta's research on Diff Authoring Time reveals a 40% reduction in coding time due to AI, shifting the primary currency of software engineering from code generation to intent specification and validation. This analysis explores how high-fidelity telemetry enables rigorous A/B testing of developer tools and identifies new bottlenecks in the agentic workflow.
An analysis of how engineering teams can scale AI-assisted development without sacrificing reliability. Key insights focus on the critical role of human ownership, the shift from code creation to review bottlenecks, and the necessity of robust observability and CI/CD foundations to support agentic workflows.
An executive analysis of Anthropic's strategic shift toward customizable agent harnesses, the operational impact of Claude Tag on enterprise workflows, and the critical security implications of frontier model capabilities. This brief outlines actionable frameworks for leveraging agentic coding, managing multi-player AI interactions, and navigating the emerging 'Pacing the Frontier' safety consensus.
Maggie Appleton explores the convergence of design and engineering in the AI era. Learn how to leverage agentic coding for rapid prototyping, why physical sketching remains critical for spatial reasoning, and how to define product nouns for complex AI tools.
An executive analysis of the shift from manual coding to agentic software factories. This brief examines the critical need for human oversight in AI-generated code, the risks of architectural drift, and the strategic value of codifying engineering taste into reusable skills and context.
TESOL demonstrates how shifting from manual coding to agentic loops increases PR volume by 850 per week while improving quality. This analysis details the strategic transition from skills to autonomous factories, emphasizing context-centric governance and verifiable standards for enterprise scalability.
Principal Engineer Lada Kessler shares advanced strategies for agentic coding, including the 'centrifuge' refinement loop, skill-based activation, and deterministic verification. Learn how to manage AI complexity, enforce honest output, and build trusted software factory building blocks.
The Datadog AI developer experience program shows how agentic coding scales from tool adoption to governed workflow. The company used evals, context hygiene, and team ownership to reduce risk in code review and model selection. The result is a practical framework for engineering leaders who need measurable, cost-aware AI development.
TESOL reports that 65 to 70 percent of pull requests now flow through an autonomous dark factory. The system uses Linear tickets, sandboxed coding agents, CI checks, and layered verification to ship code with minimal human review. The model shifts engineer work from writing code to defining scope, context, and quality guardrails. This creates a scalable operating model for AI native software teams.
Anthropic's Boris Cherny details the Opus 5 release, highlighting autonomous long-horizon tasks, prompt injection immunity, and the strategic shift toward empirical model elicitation. Learn how to leverage dynamic workflows and product overhang to build next-generation agentic products.
The discussion examines how reusable agent skills create a new software supply chain and why prompt injection is a critical enterprise risk. Snyk and Tessal are integrating automated skill scanning, versioning, and security scores into registries to support safe adoption. The analysis outlines governance controls for internal skills, credential management, and agent behavior guardrails. These practices help CISOs approve agentic coding rollouts without sacrificing developer productivity.
Anthropic's Claude Tag shifts agentic coding from single-player IDEs to multiplayer Slack environments. This analysis covers the 65% PR automation metric, the 'Dreaming' memory feature, and the strategic shift toward asynchronous, trust-based development workflows.
An executive analysis of the shift from interactive AI coding to autonomous loop engineering. Learn how to build composable software factories, optimize agent costs, and leverage verifiers to scale agentic workflows without sacrificing control.
Analysis of AI Native DevCon 2026 highlights, focusing on the strategic shift from vanity metrics to business outcomes. Covers harness engineering, agentic workflow bottlenecks, and the critical role of change management in scaling AI adoption across enterprise teams.
The sudden removal of Anthropic's Fable 5 model highlights the risks of centralized AI dependency. This analysis explores how enterprises are pivoting to open-source Chinese models, redefining engineering discipline, and leveraging domain expertise to maximize AI ROI.
Jellyfish data reveals a 2x increase in merged pull requests but highlights the 'agentic barrier' of human attention limits. Engineering leaders must shift from output metrics to business outcomes to satisfy CFO scrutiny in 2026.
Rod Johnson argues against the Python-centric AI narrative, advocating for Java-based enterprise AI integration. He details the Embabel framework's use of deterministic GOAP planning to ensure explainability and control in agentic workflows, challenging the 'vibe coding' approach.
Industry leaders from Stripe, OpenAI, and Google DeepMind discuss the obsolescence of traditional CI/CD in the age of AI agents. Key insights cover harness engineering, context optimization, and the strategic shift toward specialized open models for enterprise deployment.
An analysis of emerging trends in AI agent development, focusing on the shift from simple assistants to digital employees and specialized niche markets.
Explore how 'Semantic Anchors' and 'Semantic Contracts' can dramatically increase the precision and maintainability of AI-driven software architecture and coding.
An analysis of the latest advancements in AI coding agents, new model releases from Anthropic and OpenAI, and the critical bottlenecks in GPU compute and data center legislation. It highlights the shift from 'vibe coding' to professional agent orchestration and the emerging enterprise security risks associated with shadow AI.
A senior engineer shares practical strategies for mastering agentic coding workflows. Learn how to optimize context windows, implement automated rule checks, and leverage skills to boost software development velocity and quality.
An executive analysis of agentic software development, highlighting the critical role of engineering maturity, context management, and containerization. Learn why high-maturity teams outperform low-maturity ones and how to mitigate hallucination risks in enterprise AI adoption.
Felmo's CTO details the strategic shift from Cursor to Claude Code to manage API costs while maintaining high output. The analysis covers the reduction of human-in-the-loop processes, the rise of AI-generated code, and the evolution of developer roles in a tech-enabled veterinary startup.
An executive analysis of METR's time horizon metrics, the impact of Opus 4.5 on developer productivity, and the strategic implications of compute constraints on AI capability growth. This brief covers independent threat modeling, the shift to agentic coding, and the limitations of current benchmarking methodologies.
An executive analysis of how Felmo leverages GenAI to reduce headcount while maintaining output. The CTO details the shift from Cursor to Claude Code for cost efficiency, the elimination of manual QA loops, and the strategic focus on ROI-driven product development in a tech-enabled service model.
