Agents Make All Software Viable, Exploding Engineer Demand
AI agents economically justify building software previously too costly, filling the full circle of needed automation and boosting demand for AI engineers. Start with 24/7 support, compressed research, info surfacing, and toil elimination agents today.
Agents Unlock Economically Viable Software, Ensuring More Engineering Jobs
Traditional software couldn't cover all automatable tasks due to high costs from hardcoded business logic and if-statements. Agents change this: they make the full "circle of software that should exist" viable without massive upfront effort. Result? Exploding software volume. Companies shift from buying SaaS to building custom agents, dubbed the "SaaS copocalypse," creating more work for engineers despite faster build times. This tests software market elasticity—the cheaper software gets, the more gets built—with no S-curve slowdown yet as agents improve. Engineers thrive: next-gen juniors excel natively, veterans adapt. Vercel sees 60% of vercel.com pageviews from AI agents last 7 days, APIs/CLIs overtaking UIs, proving agents as primary users.
Build These Proven Agent Archetypes for Immediate ROI
Skip advanced coding agents; target low-hanging fruit saving millions without process overhauls:
- 24/7 Support Agents: Automate non-stop tasks humans can't (they sleep). Agent-as-a-service startups like Decagon target support; in-house versions achieve 90% deflection (handle routine queries like credit card issues real-time). Vercel's sales agent routes 75% of "contact sales" to support instantly, others to reps after LinkedIn/Google research—cuts 15min human toil per lead.
- Compressed Research: For event → research → human decision flows, agents handle research only. Vercel uses for sales leads (company size check) and abuse reports (site validation). Shrinks 30min to 5min per instance; at 100k/year scale, massive savings, zero risk/process change.
- Surface Existing Info: Pull scattered data (Slacks, Granola recordings) to update issue trackers automatically. Agents pre-research manager queries like "latest updates," making latent info usable.
- Eliminate Toil: Ask "What do you hate most?" Build agents for it. Vercel support team job satisfaction soared post-90% deflection agent, freeing them for interesting cases.
These ship fast, leverage agents' strengths (no sleep, fast research), deliver ROI now.
Infrastructure Must Evolve for Agent Builders and Users
Apps now built/used by agents demand new infra:
- Sandboxes Everywhere: Agents need computers without real ones—e.g., author's TypeScript bash interpreter (nanosecond startup) or market innovations. Expect conference deep dives.
- Agent-Friendly APIs/CLIs: UIs cheap; prioritize automation. Prod infra must "just run" agent-written code without owner tweaks.
- Security Paradigm Shifts: 1999-like vulnerabilities loom. Most agent harnesses fail by colocation (harness + generated code same runtime); separate like Anthropic's new product. Stay open to shifts beyond general sandboxes.
Europe's AI Engineering Leadership Thrives Model-Independently
Application layer (agents) stable atop commoditizing models (Cloud, Codex cheapen fast; Google leads infra pricing). Europe leads here—no model lab needed: Vercel AI SDK (10M downloads/week, Berlin-led), Pi (Austria coding agent), Open Claw. Two futures: labs monopolize (unlikely, keeps AI expensive); or commoditization empowers engineers' value-capture. Build independent of model X vs Y.