Arguments about DevRel in the AI era appear across blog posts, podcasts, conference talks, and trade-press essays. They range from a strategic expansion of the discipline to claims that agents will make much of it unnecessary. Compare them by the evidence they use and by what they assume developers, agents, and companies will continue to need.
The strategic-reframe camp
An optimistic argument for expanding the function.
Angie Jones: How DevRel is Leading AI Adoption (2025)
Direct response to the “DevRel is dead” framing of 2022 to 2024:
“A couple years ago, everyone was asking if DevRel was dead… Well, plot twist: we’re not dead. We’re standing on the biggest stage of our careers.”
Her argument:
- Developers using AI need to see real engineers learning AI-augmented practice in public, not polished demos.
- AI is non-deterministic; developers learn most from failure-recovery sequences, which only humans can model authentically.
- DevRel’s job is to define the culture of AI adoption: what good looks like, how to evaluate, how to debug, when to override.
- Published content remains available after its authors and readers move between companies.
AngelHack: Developer Relations in 2026: Four Strategies For The AI Era
Argues that the LLM is now the “first-touch user” of any developer product, reframing the function:
- “Gaps in your docs don’t just frustrate developers anymore. They create gaps in AI-assisted adoption before a human ever enters the picture.”
- API design now concerns DevRel and engineering.
- “Prompts are the new support tickets”: when ~65% of developers report AI coding assistants missing relevant context, that signals a documentation problem.
- Higher-trust DevRel work (community strategy, developer-empathy research, product-feedback synthesis) is increasingly the DevRel job; the lower-leverage activities (tutorial production, generic content) commoditise.
Doc-E AI: The Future of AI in Developer Relations
Positions AI as augmenting DevRel work rather than replacing it:
- AI tools assist with content drafting, community-signal detection, personalisation at scale.
- Humans remain irreplaceable for trust, authenticity, technical credibility, and strategic relationships.
- The successful 2025 to 2026 DevRel professional uses AI as leverage but maintains human-led work at the audience interface.
Shawn “swyx” Wang and the AI Engineer position
While not strictly framed as a DevRel argument, swyx’s positioning of the AI Engineer identity (and the entire Latent Space corpus) functions as a perspective on what DevRel for AI products should look like:
- A new category of developer is forming; they need different content, different community spaces, different tooling.
- The AI Engineer Summit, the Latent Space podcast, and the AI Engineer Foundation have institutionalised the identity.
- DevRel teams whose products serve AI Engineers must engage on AI-Engineer-specific channels.
The “DevRel as practised had to die, and is being rebuilt” camp
This position predates the current AI debate and arose during the 2022 to 2024 layoff wave.
MB Consulting: RIP DevRel 2010 to 2024: Why It Died and How to Stop Killing It
A 2024 post-mortem arguing:
- This account attributes DevRel’s decline to companies’ misuse of the function rather than AI.
- “DevRel is not marketing. Sure, it can work with marketing, but reducing it to a lead-generation tool is like asking a Michelin-starred chef to sling burgers at a drive-thru.”
- Teams reduced to content marketing are cut in this account, while programmes with a defined strategic function survive.
This argument is compatible with the strategic-reframe camp, but it attributes the failure to misuse rather than to AI itself.
Mary Thengvall’s evolving framing
Through her DevRel Weekly newsletter, Community Pulse podcast appearances, and consulting work, Thengvall has been consistent that:
- DevRel that can’t articulate business value will keep getting cut.
- AI doesn’t change the fundamental need for the function; it changes the operational mix.
- Developer Qualified Leads (DQLs) and AAARRRP-style strategy frameworks remain the basis of her approach.
Her current work combines strategic clarity with operational changes for AI-era DevRel.
James Governor and RedMonk
The RedMonk perspective, articulated across blog posts and conference talks by Governor and Stephen O’Grady, has consistently been:
- Developers remain the most important constituency in tech procurement: the Kingmakers thesis from 2013 has only been reinforced by AI.
- AI tools amplify whichever developer products are already authoritative on the open web.
- The companies that built strong open-source-led, community-led, content-rich DevRel functions in 2015 to 2022 are reaping disproportionate AI-era benefits.
The “Agent Experience is the new DX” camp
This position focuses on changes to APIs, documentation, tools, and team responsibilities.
Anthropic developer-facing essays
Taken together, Anthropic’s engineering posts and product interfaces from 2024 to 2026 imply these positions:
- Documentation written for agents matters as much as documentation written for humans.
- MCP is a primary developer-facing surface, not a side project.
- Cookbook-style repositories with complete runnable examples outperform polished marketing material for adoption.
- The same content can serve both audiences if the structural craft is right.
Mintlify product team
Mintlify’s blog and product features from 2024 onward make a related argument:
- Documentation is increasingly read by machines; tools should serve that reality.
llms.txtandllms-full.txtauto-generation should be a default feature, not a premium add-on.- Documentation platforms must serve dual audiences and shouldn’t ask the customer to choose.
Latent Space community
A continuing thread of AI Engineer Summit talks and Latent Space podcast episodes has developed a practical vocabulary for AX, tool naming, MCP design, evals, and observability. DevRel teams at AI-adjacent companies use those concepts in their operating plans.
The “Sentiment vs telemetry” camp
Faros AI’s Sentiment surveys aren’t enough in the AI era
Argues that developer sentiment about AI productivity (“I love this tool, it makes me so much faster”) consistently overstates measured productivity gains, especially when measured behaviourally rather than perceptually.
The DevRel implication is to supplement post-event surveys and post-launch NPS with behavioural telemetry.
JetBrains HAX study (April 2026)
Two-year telemetry study of 800 developers using AI assistants. Headline finding:
- Developers using AI write more code, but spend over a third of their time editing AI suggestions.
- Edit frequency increased substantially even though developers perceived minimal change.
- Time savings averaged 3.6 hours per week; daily users showed 60% higher PR throughput.
- Trust gaps persist.
For DevRel, the study supports treating survey data as one measure rather than as a substitute for observed behaviour.
Anthropic’s skill-formation research
Flags that AI assistance both accelerates work on already-known skills and may hinder the formation of new ones. Education teams can test whether learners retain the ability to explain and debug their work; infrastructure teams can monitor whether users need different support after agent-generated integrations.
The critical / sceptical camp
Sceptical analyses of common 2024 to 2026 claims.
Signals.sh: Does llms.txt actually work? (2026)
Two empirical studies through 2026 found no measurable lift in AI citations correlated with publishing llms.txt. Zero documented AI bot fetches of llms.txt files in production server logs.
Implication: much of the “AI-era DevRel” advice is unvalidated. Some of it is performative.
The “DevRel is dead because AI” thread
A persistent strand of argument visible in trade press and individual Substacks through 2024 to 2026, varying in seriousness:
- AI generates all the content DevRel produces, so why pay for DevRel?
- AI answers developer questions, so community management is obsolete.
- AI writes the docs, so technical writers are unnecessary.
These claims overreach when they treat content production as the whole function. AI can automate some drafting and first-line support, while moderation, technical judgement, relationships, and internal representation still require accountable owners.
The “DevRel as marketing channel” critique
This critique continues the 2022 to 2024 layoff debate. It argues that cheaper content generation weakens programmes measured mainly by publication volume and increases the relative value of relationships, moderation, technical judgement, and product feedback.
The “founder-led” camp
This position appears mainly in founder-led AI-product companies.
Patrick Collison (Stripe), Guillermo Rauch (Vercel), Mitchell Hashimoto
Founder-led DevRel gives an argument an identifiable author with a public record of product decisions. Early-stage AI-product companies commonly use founders in this role; see Founders as DevRel.
Harrison Chase (LangChain), Jerry Liu (LlamaIndex), Clem Delangue (Hugging Face)
AI-product founders functioning as the primary DevRel voice for their respective companies through 2023 to 2026. Their pattern: heavy in-public writing, frequent podcast appearances, candid discussion of product evolution, sustained presence in technical communities.
This group treats the founder as the most direct source for near-term product direction, although other leaders may also own those decisions.
Points of overlap
Several positions share these premises:
- LLM-mediated discovery is now a substantial fraction of developer research and is growing.
- Documentation is increasingly read by AI agents, and writing for them matters.
- The lowest-leverage activities of pre-AI DevRel (generic listicles, content marketing) are being cut.
- Founders, senior engineers, and trusted educators remain useful sources because readers can examine their record and judgement over time.
- The evidence available in 2026 covers only the first few years of the transition.
People who agree that developer discovery is changing still disagree about the tools, measures, and organisational response.
Where to read further
- Latent Space (podcast and newsletter): swyx and Alessio Fanelli. AI-engineering interviews and analysis.
- DevRel Weekly: Mary Thengvall’s curated newsletter.
- Community Pulse podcast: DevRel-community perspectives.
- Angie Jones’s blog (angiejones.tech): How DevRel is Leading AI Adoption.
- AngelHack blog: Developer Relations in 2026 essay.
- MB Consulting blog: RIP DevRel post-mortem and follow-ups.
- Anthropic engineering blog: Practical agent-design and documentation essays.
- RedMonk blog: Industry analysis.
- AllThingsOpen DevRel track and DevRelCon talk archives: primary venues for the discourse.