---
title: "AI Agents"
description: "578 posts about AI Agents, summarised, each linking to the original."
---

# AI Agents
> 578 posts about AI Agents, summarised, each linking to the original.

## Articles

### [Best practices for coding with agents](https://yomu.fyi/post/best-practices-for-coding-with-agents.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Lee Robinson
- Published: Jan 9, 2026
- Type: Tutorial

Cursor's guide presents practices for using coding agents that can run for hours, complete multi-file refactors, and iterate until tests pass. Planning first is emphasized: Plan Mode researches the codebase, asks clarifying questions, creates a reviewable implementation plan, and waits for approval. The guidance recommends letting the agent discover context, starting new conversations when focus declines, and using Rules for persistent project instructions while Skills provide dynamic workflows. It also describes hooks for long-running loops, worktrees for isolated changes, parallel model runs, cloud agents, and Debug Mode's hypothesis-and-instrumentation process. Careful diff review, specific prompts, and verifiable goals remain necessary because generated code can be subtly wrong.


### [Code And Let Live](https://yomu.fyi/post/code-and-let-live.md)
- Company: [Fly.io](https://yomu.fyi/company/fly-io.md)
- Published: Jan 9, 2026
- Type: Announcement

Code And Let Live argues that read-only, ephemeral sandboxes are the wrong abstraction for coding agents, which need durable computers rather than fresh containers for every task. It introduces Sprites, disposable cloud computers that provide root Linux shells, 100GB of initial capacity, HTTPS through an Anycast network, automatic idle shutdown and metering stops, and persistence until explicitly removed. Sprites can be checkpointed and restored in about a second, allowing interactive recovery after changes while retaining installed software and development state across days or months. The argument extends beyond developer workflows: durable agents can keep realistic application context, observe logs, and support personal software whose development and production environments are the same, although the post says Sprites are unsuitable for applications serving millions of users.


### [Dynamic context discovery](https://yomu.fyi/post/dynamic-context-discovery.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Jediah Katz
- Published: Jan 6, 2026
- Type: Explainer

Cursor describes dynamic context discovery, a coding-agent pattern that provides fewer details initially and lets the agent retrieve relevant information instead of injecting everything as static context. The approach uses files as a simple interface: long tool responses, chat history, Agent Skills, MCP tool descriptions, and integrated terminal output are stored or synchronized so the agent can inspect only what it needs with tools such as tail, grep, rg, and jq. For MCP, only tool names are included initially, while descriptions are synced into one folder per server; an A/B test found a 46.9% reduction in agent tokens for runs that called an MCP tool, with high variance based on the number of MCPs. Cursor says the design reduces context bloat, preserves information truncation could lose, supports recovery after summarization, and can expose MCP re-authentication status. The changes are planned to become available to all users in the coming weeks.


### [New research: Customer service team evolution](https://yomu.fyi/post/new-research-customer-service-team-evolution.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Emiliano Melchiorre
- Published: Jan 5, 2026
- Type: Explainer

An analysis of 166 interviews examines how customer service roles, workflows, and team structures changed after adopting Fin or similar AI agents. Using interviews with Intercom customers or prospects, the researchers cleaned conversation transcripts with Python and coded them through the OpenAI API against a closed codebook. Workflow disruption was reported by 94.58% of participants, while 82.53% reported changed responsibilities; 27.71% reported headcount or hiring effects, and 6.02% reported changed team structures or reporting lines. The findings describe hybrid human–AI operations in which AI handles triage, routing, translation, repetitive responses, and some refunds, while people increasingly oversee quality, testing, metrics, and complex or sensitive interactions, although organizational strategies and required skills remain uneven.


### [Steam, Steel, and Infinite Minds](https://yomu.fyi/post/steam-steel-and-infinite-minds.md)
- Company: [Notion](https://yomu.fyi/company/notion.md)
- Author: Ivan Zhao
- Published: Dec 22, 2025
- Type: Explainer

The post frames AI as a new “miracle material” that could reshape knowledge work as steel and semiconductors reshaped earlier eras. It argues that coding agents already let one programmer orchestrate several AI coding agents, but broader knowledge work remains constrained by fragmented context across tools and weak verifiability. At the organisational level, it compares AI with steel and steam, suggesting agents could preserve workflow context, surface decisions, and reduce dependence on meetings and hierarchical approvals; Notion is described as using more than 700 agents alongside 1,000 employees for repetitive tasks. At economy scale, it predicts organisations spanning humans and thousands of agents, with continuous workflows and new rhythms, while acknowledging that this transition may be disorienting and requires redesign rather than simply adding chatbots to existing tools.


### [First Block – Tools & craft – Notion](https://yomu.fyi/post/first-block-tools-craft-notion.md)
- Company: [Notion](https://yomu.fyi/company/notion.md)
- Published: Dec 22, 2025
- Type: Announcement

First Block is a set of conversations with founders and company leaders across legal technology, finance, career access, software development, talent, go-to-market, and developer tools. The episodes feature Gabe Pereyra of Harvey, Gerry Giacomán Colyer of Clara, Garrett Lord of Handshake, Jesse Zhang of Decagon, Fabian Hedin of Lovable, Brendan Foody of Mercor, Varun Anand of Clay, and Michael Truell of Cursor. Topics include deploying AI agents in finance operations across Latin America, democratizing software development and career opportunities, intentional customer discovery, and building for current AI capabilities. The collection also covers founder-led selling, product-market fit, specialized go-to-market platforms, commercial thinking, startup pivots, and departures from conventional startup advice.


### [Make with Notion Showcase Europe 2025: Highlights & Takeaways](https://yomu.fyi/post/make-with-notion-showcase-europe-2025-highlights-takeaways.md)
- Company: [Notion](https://yomu.fyi/company/notion.md)
- Author: Áine Dundas
- Published: Dec 18, 2025
- Type: Announcement

Make with Notion Showcase Europe 2025 brought more than 1,300 attendees across four cities during the second year of the in-person conference series. The event centered on three themes: agentic AI taking action, organized knowledge enabling effective AI, and a community building AI-powered work. Notion presented Notion 3.0, whose Agent can handle multi-step workflows, and previewed Custom Agents that can be shared across teams, scoped to databases or teamspaces, and triggered by schedules or events. With MCP integration, Notion content and connected app context can be accessed from other tools; Custom Agents are in early access and planned for broader availability in early 2026. Research cited losses of up to €16,000 per employee annually in the UK, France, and Germany from searching for scattered information, while customer sessions covered knowledge management, AI workflows, and Notion implementations.


### [2026 customer service planning series: Vol. 05](https://yomu.fyi/post/2026-customer-service-planning-series-vol-05.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Declan Ivory
- Published: Dec 16, 2025
- Type: Explainer

AI-first customer service makes capacity planning less predictable because automation changes volume, work mix, human responsibilities, and performance over time. The proposed planning model puts automation rate—AI Agent involvement rate multiplied by AI Agent resolution rate—alongside inbound volume, human output for complex remaining work, and occupancy. It recommends ambitious automation assumptions only when backed by named ownership, content and systems investment, work-type targets, and staged improvement, while modeling lower cases closed per person and more time for off-queue work. Finance should treat the plan as a revisable set of assumptions, review it at least quarterly, and avoid cutting headcount before automation is proven. Surplus capacity should be redirected to AI improvement, product feedback, new channels, or proactive customer experience work rather than automatically reduced.


### [Introducing Debug Mode: Agents with runtime logs](https://yomu.fyi/post/introducing-debug-mode-agents-with-runtime-logs.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Alexey Kozy & Albert Slepak
- Published: Dec 10, 2025
- Type: Announcement

Debug Mode is an agent loop for coding bugs that combines runtime information with human verification, addressing issues that can stump conventional coding agents. After the user describes a bug, it reads the codebase, proposes multiple hypotheses, and instruments the code with logging statements designed to test them. The user reproduces the issue while the agent collects variable states, execution paths, and timing information, then uses those logs to identify a root cause and produce a targeted fix, often a two- or three-line modification. The user reproduces the bug again with the fix; if it works, the agent removes its instrumentation, while a failed verification prompts additional logging and refinement until the user considers the problem solved.


### [2026 customer service planning series: Vol. 04](https://yomu.fyi/post/2026-customer-service-planning-series-vol-04.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Declan Ivory
- Published: Dec 9, 2025
- Type: Explainer

After defining team roles, an operating model is needed to make progress part of customer-support work and keep an AI Agent improving over time. The stated goal is that “the first time you answer a question should be the last,” with each resolution improving the system so fewer issues repeat, quality compounds, and support scales. The post emphasizes clear ownership, risk-aware guardrails, feedback loops, and a culture that values improvement work; it identifies ambiguity as a common cause of performance plateaus. An AI ops lead, often located in support operations or developed from an existing role, owns performance and drives change, illustrated by Dotdigital’s dedicated specialist after resolution volume held at about 2,800 conversations per month for three months; lightweight governance is presented as a way to keep iterating without excessive bureaucracy.


### [Setting the standard for support: What Spain’s new customer service law signals](https://yomu.fyi/post/setting-the-standard-for-support-what-spain-s-new-customer-service-law.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Peter Dalton
- Published: Dec 8, 2025
- Type: Explainer

Spain’s proposed customer service law would impose stricter requirements on regulated providers and sufficiently large companies, covering response times, human access, complaint handling, accessibility, and auditability. It would require 95% of support calls to be answered within three minutes, free lines, 24/7 support for continuity issues in essential services, and complaints resolved within 15 days or five days for undue charges. The source also describes protections against spam calls, centralized complaint records, multilingual support obligations for some large companies, and simpler subscription cancellation. It presents AI Agents such as Fin as a way to reduce avoidable volume, answer calls, preserve human escalation, structure complaints, communicate outages, and support reporting. The stated conclusion is that early modernization may ease pressure on human teams while helping organizations adapt to rising regulatory and customer expectations.


### [Intercom achieves AIUC-1 certification: A new standard for trust in AI Agents](https://yomu.fyi/post/intercom-achieves-aiuc-1-certification-a-new-standard-for-trust-in-ai.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Thibault Candebat
- Published: Dec 8, 2025
- Type: Announcement

Intercom announces that it has achieved AIUC-1 certification, describing it as the first standard designed specifically for AI Agents. The certification complements broader frameworks such as ISO 42001 and addresses enterprise concerns spanning security, customer safety, system reliability, data and privacy, society, and accountability. Organizations seeking AIUC-1 undergo independent third-party audits and quarterly adversarial testing across more than a thousand enterprise risk scenarios, while the standard itself evolves quarterly through the AIUC-1 Consortium. Intercom says the certification extends its governance approach to Fin, its AI Agent, providing independent validation that its AI systems are safe, resilient, regularly tested, safeguarded, and enterprise-ready; it also identifies Intercom as a founding technical contributor to the standard.


### [Improving Cursor’s agent for OpenAI Codex models](https://yomu.fyi/post/improving-cursor-s-agent-for-openai-codex-models.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Cursor
- Published: Dec 4, 2025
- Type: Problem & solution

Cursor describes adapting its agent harness for OpenAI's latest frontier coding model, GPT-5.1-Codex-Max, by pairing model-familiar instructions with Cursor-specific tools and tuning against Cursor Bench. The Codex integration adopts a more shell-forward design, aligns tool names with commands such as rg, explicitly prefers tools over shell commands, and uses sandboxing to limit unauthorized file and network access. It also limits reasoning summaries to one or two sentences, gives literal guidance for invoking read\_lints after substantive edits, removes mid-turn user-communication language, and biases the agent toward taking action unless a plan is requested. Preserving Responses API reasoning items is treated as critical: Cursor reports a 30% performance drop for GPT-5-Codex when traces were removed, compared with OpenAI's observed 3% SWE-bench degradation for GPT-5, while prompt-ordering lessons led it to remove wording that discouraged ambitious work.


### [2026 customer service planning series: Vol. 03](https://yomu.fyi/post/2026-customer-service-planning-series-vol-03.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Declan Ivory
- Published: Dec 2, 2025
- Type: Explainer

AI performance in customer support can drift without clear ownership, even when the underlying model is capable. This part of a 2026 planning series presents four roles: AI operations lead, knowledge manager, conversation designer, and support automation specialist. The roles cover monitoring and guardrails, structured and compliant knowledge, conversational tone and flow, and reliable action through backend systems, with the AI operations lead coordinating reporting and improvement. The post describes an operating loop in which performance patterns drive knowledge fixes, interaction changes, and expanded automation, while phased ownership moves from part-time assignments to formal roles and hiring. It says dedicated specialization becomes essential when AI handles 50–70% of incoming volume, and frames these roles as the backbone of an AI-first support organization.


### [2026 customer service planning series: Vol. 02](https://yomu.fyi/post/2026-customer-service-planning-series-vol-02.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Declan Ivory
- Published: Nov 25, 2025
- Type: Explainer

When AI Agents resolve most customer conversations, support organizations need to move beyond tiered models centered on queues, handoffs, and volume-based productivity. The proposed AI-first operating model distributes four foundational responsibilities: an AI operations lead monitors and improves performance, a knowledge manager maintains structured content, a conversation designer shapes communication and handoffs, and a support automation specialist builds executable workflows. Existing enablement, QA, workforce management, and leadership roles also evolve, with player-coach leaders managing both AI performance and people. Examples from Dotdigital, Clay, Lightspeed, and Intercom illustrate dedicated roles and an Intercom structure organized around Human Support, AI Support, and Support Operations and Optimization.


### [SpellVault’s evolution: Beyond LLM apps, towards the agentic future](https://yomu.fyi/post/spellvault-s-evolution-beyond-llm-apps-towards-the-agentic-future.md)
- Company: [Grab](https://yomu.fyi/company/grab.md)
- Author: Felix Haryanto Lie
- Published: Nov 21, 2025
- Type: Explainer

SpellVault began as Grab’s no-code platform for building LLM apps, using Retrieval-Augmented Generation (RAG) and plugins to connect applications with knowledge sources and external systems. Users could ground responses in Wikis, Google Docs, text, and PDFs, invoke custom HTTP endpoints, and access apps through the web, Slack, or APIs. The platform later added citations, Python execution for mathematical problems, scheduled actions, and drag-and-drop Workflows combining LLM calls, code, and Knowledge Vault lookups, while its executor moved toward graphs with nodes, edges, and states. SpellVault now exposes apps and RAG through MCP, allowing external agents and compatible clients to invoke apps and search, retrieve, or add Knowledge Vault information; TinyMCP adds MCP capabilities to FastAPI as a router.


### [Intercom is now a Shopify Plus Technology Partner](https://yomu.fyi/post/intercom-is-now-a-shopify-plus-technology-partner.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Gayathri Padmanabhan
- Published: Nov 19, 2025
- Type: Announcement

Intercom announces that it is now a certified Shopify Plus Partner on the Technology Track. The program recognizes technology providers whose product quality, service, performance, privacy, and support meet advanced requirements for Shopify Plus merchants. Intercom says its integration is vetted and optimized, and describes recent additions including Data Connector templates for Fin, multi-store support, inbox order actions, EU workspace support, and updated data mapping and custom fields. The announcement also lists planned expanded Fin Tasks, Model Context Protocol support, and smarter product search powered by Shopify data, positioning these capabilities as ways to resolve ecommerce support requests faster and personalize conversations at scale as merchants prepare for peak season and rising customer expectations.


### [First Block with Jesse Zhang, Co-founder and CEO of Decagon](https://yomu.fyi/post/first-block-with-jesse-zhang-co-founder-and-ceo-of-decagon.md)
- Company: [Notion](https://yomu.fyi/company/notion.md)
- Author: Anastasia Crew
- Published: Nov 19, 2025
- Type: Explainer

The episode profiles Jesse Zhang, co-founder and CEO of Decagon, whose AI agents support customer service and reportedly achieve 70–80% deflection rates and 3x improvements in customer satisfaction. In its first 18 months, Decagon prioritized short-term execution and customer deployment, then shifted toward longer-term thinking; the source says this helped it move from stealth to unicorn status in a year. Zhang also describes intentional customer discovery, Agent Operating Procedures (AOPs), enterprise trust, and the need to pair technical excellence with commercial thinking. He credits senior generalists from his network with establishing an early team foundation that supported growth from 12 to 200 people in 18 months, while cautioning against applying generic advice instead of judging personal strengths and timing.


### [2026 customer service planning series: Vol. 01](https://yomu.fyi/post/2026-customer-service-planning-series-vol-01.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Declan Ivory
- Published: Nov 18, 2025
- Type: Explainer

Part one of a five-part 2026 customer service planning series argues that support organizations must be redesigned around AI rather than adding AI to existing tools, processes, and org charts. It frames AI Agents as end-to-end resolution engines and infrastructure that can serve as the first and last touchpoint, manage workflows, orchestrate handoffs, and take actions. The proposed mindset shift includes planning for changing work distribution, treating support as a product function, measuring resolution, impact, and system reliability, and assigning clear ownership for agent performance and continuous feedback. The post also says teams should give AI increasingly complex workflows while people improve the system, creating compounding returns. It concludes that adaptability will be essential as AI evolves, and previews a future edition on designing the resulting support organization.


### [The productivity impact of coding agents](https://yomu.fyi/post/the-productivity-impact-of-coding-agents.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Author: Oskar Schulz
- Published: Nov 11, 2025
- Type: Benchmark

The study examines how developers use Cursor’s agent and how its adoption affects software productivity across tens of thousands of users. After the agent became the default for eligible organizations, the rate of merged pull requests increased 39% relative to time trends in a baseline group, while revert rates did not change significantly, bugfix rates slightly decreased, and average lines edited and files touched per merged pull request were unchanged. Agent acceptance varied with experience: each standard-deviation increase in years of experience corresponded to an approximately 6% increase in acceptance relative to the mean, and experienced developers were more likely to plan before coding. In a sample of 1,000 users, about 61% of conversation-starting requests concerned implementation, with others focused on explanation or planning. The authors say no single metric yet captures AI’s economic impact on software engineering.


[Newer posts](https://yomu.fyi/topic/ai-agents/page/26.md) · [Older posts](https://yomu.fyi/topic/ai-agents/page/28.md)