Development in 2026: Citizen Builders, AI Agents, and Code as the New Latin
Software creation is widening. AI has pushed app building into everyday teams, and that shift comes with governance, security, and skills gaps you can't ignore. Here's what leaders and practitioners should expect in 2026-and what to do now to stay ahead.
Citizen developers will outnumber pros
Expect business users to outpace professional developers by a wide margin. One CEO projects a 4:1 ratio by 2026 as employees spin up AI-driven apps, automations, and workflows inside their departments.
The result: a surge of shadow tooling. Enterprises could be running thousands of AI-built artifacts, with a majority invisible to central IT and security. Departments won't replace core platforms, but each team will have a few "quiet builders" who become crucial internal problem solvers.
Low-code delivers speed-and a new legacy problem
Low-code solved speed, then exposed maintenance. Without oversight, many organizations are already stuck with applications no one can support or scale. That's technical debt, just with friendlier UIs.
As citizen tools spread, expect IT teams to inherit fragmented automations, brittle integrations, and unclear ownership. The fix isn't to shut it down-it's to govern it.
Developers shift from creators to curators
AI has increased code volume to a point where manual review can't keep up. Several leaders expect the developer role to tilt toward curation, validation, and tool orchestration instead of line-by-line creation.
That means adopting advanced testing, static analysis, and policy-as-code at scale. CISOs and engineering leaders should partner on the automation needed to vet AI-generated code across repos and services, not just add more checklists.
Security risk rises with AI-written code
More AI-written code means more vulnerabilities slipping through, often without clear attribution. "Vibe coding" will spread: prompts over patterns, speed over traceability. Security review processes aren't built for this volume or abstraction layer.
You'll need gating at commit, PR, and deploy. Shift-left can't be a slogan-it needs enforceable controls, developer-centric DX, and training that rebuilds the critical eye some teams are already losing to over-reliance on assistants.
- Adopt clear policies for AI usage and disclosure in commits.
- Require SAST/DAST/IAST plus SBOM generation for all services.
- Gate merges with quality and security score thresholds.
- Instrument runtime with anomaly detection tied to deploys.
Useful references: OWASP ASVS and NIST SSDF.
Apps get redefined: prompts, modules, and AI as the OS
Several experts expect apps to shift from monolithic, declarative logic to temporary, purpose-built modules spun up from prompts. Think fewer dedicated front-ends, more on-demand helpers stitched into workflows.
AI agents will sit between users and backends, operating across data sources, tools, and APIs. Outcome-first replaces app-first. Fewer tabs. More orchestration.
Higher-level engineering: from "how to code" to "what to build"
Agentic coding moves us up the stack. Engineers will describe intent, constraints, and tests, while agents generate, wire, and validate most of the implementation. Platforms that manage infra, scale, and operations behind AI-built systems will matter more than the syntax itself.
That's where "code as the new Latin" lands: syntax becomes historical context. The valuable skill becomes system design, product sense, and verification rigor.
What to do now
- Create a citizen development policy: approved tools, data access scopes, review checkpoints, and ownership rules.
- Stand up a productized platform team: golden paths, templates, and paved roads for both engineers and power users.
- Instrument everything: code health metrics, dependency risk, model usage, and provenance tags for AI-generated artifacts.
- Upgrade validation: contract tests, generative test suites, mutation testing, and policy-as-code for security and compliance.
- Train for the curator role: debugging AI output, threat modeling, and prompt hygiene for reliable, repeatable outcomes.
- Budget for agents and oversight: agent platforms, observability for agent actions, approval flows, and rollback plans.
Skills to build before 2026
- AI-assisted development: code review with AI, property-based testing, spec-first workflows, and test generation.
- Security engineering: abuse-case testing, secrets management, and supply chain controls baked into CI/CD.
- Systems thinking: API contracts, data lineage, and cost-aware design for agent-heavy architectures.
- Governance at speed: change management that fits weekly ship cycles, not quarterly committees.
If you're levelling up teams on AI-enabled engineering and secure automation, these resources can help:
The bottom line
Citizen builders will be everywhere. Developers will curate more than they type. Agents will stitch systems together while security races to keep the lights on.
Treat this as an architecture and governance problem, not a hype cycle. Set the rules, ship the tooling, and train your people.
How do you see the developer role evolving? Drop your take in the comments.
Your membership also unlocks:
