How AI Is Changing the Way Students Build Experience

Introduction

Somewhere in 2025, the average undergraduate stopped describing their summer as "interned at" and started describing it as "shipped." The change of verb sounds small. It is not. "Interned" implies someone gave you an opportunity. "Shipped" implies you took one. Both can show up as a single line on a resume; only one of them shows up as a working URL.

That swap is the entire subject of this piece. The platforms below are the ones doing the actual work behind it: simulated case studies on Forage, the daily craft of a coding assistant inside an editor, the launchpad demos of a vibe-coding agent, the always-on tutor available at 3am with infinite patience and questionable accuracy. Each section presents the tool, what it actually does, what users say, and where field experience reveals it falls short. Numbers are dated where possible because pricing and limits in this category move fast.

Forage: free certificate, open access, weak credentialing signal

Forage runs more than 70 corporate-branded job simulations co-built with firms like JPMorgan, Goldman Sachs, BCG, Accenture, and KPMG. Anyone with an email can enrol. The catch is the trade between accessibility and credentialing weight, and that trade has been getting worse for the user.

What Forage actually offers

Pricing and user ratings

Where it earns its place and where it falls short

Field observation: Forage works as exposure, not credential. A pharmacy student who uses a BCG simulation to figure out whether strategy work fits comes out ahead. The same student listing four certificates as employment comes out flagged.

GitHub Copilot Student: the free plan that just got narrower

GitHub's student offering reached nearly two million verified users by early 2026. The plan stayed free in the March 2026 update; what changed was access to premium models. Anyone whose workflow relied on manually picking Claude Opus or GPT-5.4 has had to rebuild it.

What Copilot actually offers students

Pricing and user ratings

Strengths and weaknesses, by use case

Field observation: the GitHub history Copilot helps a student build is genuinely cleaner than what undergraduates produced two years ago. The fluency it removes the need to acquire is a different problem entirely, and one no recruiter is going to fix.

Replit Agent: fastest to a demo, dangerous if mistaken for production

Replit makes the path from "describe an app" to "deployed URL" shorter than any tool reviewed. That speed is also the source of its reputational damage. The SaaStr database deletion incident of July 2025 is now logged as OECD AI Incident 1152. Subsequent guardrails reduced but did not eliminate the underlying behaviour Capterra reviewers still report.

What Replit actually offers

Pricing and user ratings

Strengths and weaknesses, by use case

Field observation: Replit lives in the throwaway zone. Hackathon demos, school projects on dummy data, weekend prototypes. Anything with real users, real money, or real data should run elsewhere.

Cursor Pro: the choice once a student can already code

Cursor is a VS Code fork with an LLM threaded into every action. The killer feature is Composer for multi-file edits. Independent reviews put productivity gains at 30 to 50% on real refactor work for developers who already know what they are doing. Beginners with no foundation get a different and worse outcome.

What Cursor actually offers

Pricing and user ratings

Strengths and weaknesses, by use case

Field observation: Cursor rewards the student who already shipped something the hard way last year. It penalises the one who never has.

Headline scores cluster between 4.5 and 4.7 across the stack; the differences in what each tool actually buys are larger than the ratings suggest.

Lovable: the no-code platform with a real backend story

Lovable is the Stockholm startup that hit $100 million in annual recurring revenue within 12 months of launch, per the company's own disclosures. It is the platform a non-technical co-founder actually ships with. The genuinely differentiated detail nobody else flags is that Visual Edits, every colour change, font tweak, spacing adjustment, consume zero credits.

What Lovable actually offers

Pricing and user ratings

Strengths and weaknesses, by use case

Field observation: the workflow that has emerged on student-built MVPs is a Frankenstein chain. Prompt the app in Lovable, sync to GitHub, harden in Cursor, push back. The portfolio piece is no longer pure anything, and that is the point.

Claude and ChatGPT: the lab partner who never sleeps

RAND's December 2025 panel pegged ChatGPT at 53% of US students using it for schoolwork; Google Gemini doubled to 28% in a single year. Claude's user base is smaller but the composition is unusual. Anthropic's analysis of one million Claude student conversations found computer science students producing 36.8% of all traffic against 5.4% of US degrees, a six-times overrepresentation that compounds across every assignment.

What students actually use these for

Pricing and user ratings

Strengths and weaknesses, by use case

Field observation: the technical cohort using Claude six times more intensely than its share of degrees would predict is compounding an advantage every week. The students still pretending not to use any of these tools are not winning anything.

Where this leaves a 2026 student portfolio

LinkedIn's 2025 skills data is the bluntest aggregate signal: ChatGPT was the most-added skill on the platform with 60% of new additions among job-seekers; prompt engineering hit 38%. The Stepstone/ISE 2025 graduate recruiter survey put IT, digital, and AI skills at the top of what employers want. IntuitionLabs' 2025 review of big tech hiring noted that screening criteria have tightened around two markers: a public GitHub history with real commits, and a portfolio of shipped, deployed projects, regardless of how they were built.

A clean LinkedIn with eight Forage simulations and zero shipped code is now a weaker profile than a messy GitHub with five real, deployed, AI-augmented projects, even when the GitHub belongs to a freshman. Microsoft's 2025 cross-generational survey: 87% of Gen Z office workers say AI has helped their careers, against 76% 

Closing read

“Build experience” used to mean show up somewhere reputable for a summer and be useful. In 2026 it means assemble an artefact stack a recruiter can audit in twenty minutes. The six tools above are not interchangeable. Forage builds context. Copilot and Cursor build craft. Replit and Lovable build evidence on projects where speed matters more than polish. Claude and ChatGPT build the underlying thinking that lets the rest of the stack mean anything. Used together, the assembly is more compelling than the resume that came out of a 12‑week summer at a Fortune 500. Used naively, by a student who never debugged anything they did not delegate, the assembly is a sandcastle; the work has not disappeared, it has moved upward into specifying, judging, and explaining.

Sitting next to that stack, a learning hub like Timtis quietly changes what students actually do with these tools. Instead of bouncing between Forage certificates, half-finished Replit demos, and scattered ChatGPT chats, a student can work through structured paths that force them to turn experiments into shippable artefacts and written reflections. That kind of environment does not replace internships or projects, but it does shape them: a GitHub repository that follows a Timtis-style brief, a Lovable prototype built against a clearly defined user story, or a Claude-powered research memo that cites its sources rigorously. When a recruiter opens the portfolio, they are not just seeing “used AI tools,” they are seeing a trail of scoped problems, deliberate choices, and explanations that hold up under questions.