Thita vs Pramp: AI Interviewer vs Live Peer Practice

If you've searched for pramp alternative recently, the first thing worth knowing is that Pramp itself has changed. As of July 2024, Pramp's peer-to-peer mock interview sessions moved to a new platform called Exponent Practice — the Pramp brand still gets referenced in places, but new sessions run through Exponent. (Source: tryexponent.com/practice, checked 2026-09-07: "As of July 2024, all new Pramp sessions are hosted on Exponent Practice. It's still free and even better.")

That matters for this comparison, because "Pramp vs Thita" is really "a free live peer-matching platform vs a voice-led AI interviewer" — two genuinely different formats for the same underlying goal. This post compares them directly, with sources, so you can decide which one (or which combination) fits where you are right now.

What Pramp/Exponent actually is

Exponent Practice matches you with another candidate for a live, scheduled mock interview conducted over video. Sessions run about an hour: each of you interviews the other for roughly 30 minutes, using a built-in collaborative code editor that supports Python, JavaScript, Java, Go, C++, C, C#, Ruby and Swift for coding rounds. Round types available go beyond DSA — the platform also covers system design, behavioural, product management, finance, SQL, data science/ML, and frontend interviews. The core practice tool is free, with monthly credits; a paid membership adds unlimited sessions and AI feedback transcripts. (Source: tryexponent.com/practice, checked 2026-09-07.)

In other words: it's a real human on the other end, asking real questions, in real time — but it's also a peer, not a trained interviewer, and you need to find a partner and a time slot before you can start.

What Thita does differently

Thita's AI interviewer is available on demand — no partner, no scheduling, no waiting for a match. You talk through your approach out loud, write and run code in a real editor across six languages (Python, C++, Java, JavaScript, Go and C#), and the AI asks adaptive follow-up questions based on what you actually said and submitted. Beyond coding, Thita covers system design (scored on a canvas the AI evaluates), low-level design, machine coding, behavioural, product management, data science/AI, and resume-based interviews generated from your own CV.

Start a session at thita.ai/ai-interview.

Side-by-side comparison

Dimension	Exponent (formerly Pramp)	Thita AI Mock Interview
Format	Live peer-to-peer video, scheduled, roles rotate mid-session	AI-led, voice interviewer, available on demand
Live voice	Yes, from a peer	Yes, from the AI
Code execution	Yes, built-in collaborative editor	Yes, 6 languages
Feedback	Verbal from your peer partner; quality varies by who you're matched with	Instant written report: correctness, complexity, code quality, communication
Round types	DSA, System Design, Behavioural, PM, Data Science, Frontend	DSA, System Design, LLD, Machine Coding, Behavioural, PM, Data Science/AI, resume-based
Scheduling required	Yes — you need a matched partner and a time slot	No — start immediately
Free tier	Yes, free with monthly credits	Yes, free Starter plan forever
Price	Free with credits; paid membership for unlimited sessions + AI transcripts	Free Starter; Pro roughly USD 15/month; Elite roughly USD 30/month (see current pricing)

Sources, checked 2026-09-07: tryexponent.com/practice. Thita figures from productFacts.ts and lib/geo.ts.

Where Exponent (Pramp) genuinely wins

A real human is evaluating you. No AI system, however good, fully replicates the subtle judgement of an experienced engineer reacting to your reasoning in real time. Exponent gives you that.
Reciprocal interviewing builds a different skill. You interview your partner too, which is a genuinely useful and underrated exercise — asking good follow-up questions teaches you to anticipate them yourself.
Broad, free peer-matching at scale. The core practice tool has stayed free through the Exponent transition, and the matching pool is large enough that most candidates can usually find a partner.
Company- and role-specific matching options. You can often filter for partners targeting similar companies or roles, which real AI systems can't replicate through a shared human perspective.

Where Thita wins

No scheduling friction. You don't need to find a partner, agree on a time, or risk a no-show. A session starts the moment you're ready.
Consistency. Every session gets the same rigour of follow-up and evaluation — it doesn't depend on which peer you happened to be matched with that day, some of whom are stronger interviewers than others.
Deeper round coverage on one platform. Low-level design, machine coding, and resume-based interviews generated from your own CV aren't part of Exponent's round list.
Code execution report attached to feedback. Every submission comes with a written breakdown of correctness, complexity, and code quality alongside the communication score, generated the same way every time.
No no-shows. A scheduled peer session depends on someone else turning up on time and prepared. An AI session depends on nothing but you being ready to start.
Practice fits around your day, not a shared calendar. If your only free 20 minutes is at 11pm or during a lunch break, an on-demand format is the only one that can use it.

Who should pick which

Pick Exponent (Pramp) if: you want the specific experience of being evaluated by another human, you're comfortable scheduling around a partner's availability, and you'd benefit from also practising as the interviewer — a skill that transfers directly to your own communication as a candidate.

Pick Thita if: you want to practise right now without coordinating a partner, you want consistent evaluation criteria across every session, or you need a round type Exponent doesn't cover on the same platform, like low-level design or a resume-based interview built from your own CV.

Use both, on a schedule. A reasonable split for most candidates: use Thita for daily or every-other-day sessions where consistency and availability matter most, and book an Exponent session once or twice a week for the specific value of a live human reaction. Neither format alone tests everything a real interview does, and the two are complementary rather than redundant.

A concrete example: booking friction vs on-demand practice

Consider two candidates, both with an interview in ten days, both trying to fit in a system design mock session on a Tuesday evening after work.

Candidate A, using Exponent: opens the platform, browses available slots, and finds a partner whose availability overlaps with theirs three days out, not that evening. They book it, get a calendar reminder, and when the day arrives their partner is five minutes late. The session runs 45 minutes: 20 minutes interviewing their partner on a caching system, 20 minutes being interviewed on a URL shortener design. Feedback is verbal, given at the end, and depends heavily on how experienced their partner happens to be at giving structured feedback — some partners are excellent at this, others less so.

Candidate B, using Thita: opens thita.ai/ai-interview that same Tuesday evening, picks system design, and starts within a minute. They talk through a URL shortener design on a canvas, and the AI asks follow-ups about read/write ratios and how they'd handle a hot key. When the session ends, they get an immediate written report scoring their trade-off reasoning, their handling of the follow-up, and the completeness of their design — generated the same way it would be for any other session.

Neither experience is strictly better. Candidate A got the specific value of a human partner's live reaction and the practice of being the interviewer themselves. Candidate B got to practise exactly when they had the time, with consistent evaluation criteria and no dependency on a partner showing up prepared. The right choice depends on what's scarce for you: time and scheduling flexibility, or the specific texture of human feedback.

Common mistakes when relying on only one format

Only ever being the interviewee on Exponent. The platform's reciprocal structure means you also interview your partner — skipping that half, or treating it as a formality, wastes half the value of the session. Asking good follow-up questions is a skill that transfers directly to anticipating them yourself.
Assuming AI feedback and peer feedback measure the same thing. They overlap heavily on technical correctness but diverge on things like communication style and the visceral experience of being watched by another person — treat them as complementary signals, not interchangeable ones.
Letting scheduling friction reduce total practice volume. If finding a partner slot is the bottleneck, that's a reason to fill the gaps with an on-demand format rather than a reason to practise less overall.
Not rotating round types. Both platforms cover more than DSA — Exponent adds finance and SQL, Thita adds low-level design, machine coding, and resume-based sessions. Sticking to only coding rounds on either platform leaves the rest of a real interview loop unrehearsed.
Treating one bad peer match as evidence the format doesn't work. Peer quality varies session to session on any human-matched platform. One unhelpful partner isn't a reason to abandon peer practice entirely, any more than one easy AI session is a reason to trust you're fully prepared.

Frequently asked questions

Is Pramp still around, or has it shut down?

Pramp hasn't shut down, but new sessions have moved to Exponent Practice as of July 2024. The underlying free peer-matching format is the same; the brand and platform changed.

Is Exponent (Pramp) actually free?

Yes, the core practice tool is free with monthly credits, according to Exponent's own practice page. A paid membership adds unlimited sessions and AI feedback transcripts.

Does Thita replace live peer interviews entirely?

Not necessarily — a live human reacting to you in real time is a genuinely different experience than an AI interviewer, and some candidates value that specifically. Thita's AI interviewer is best thought of as the on-demand layer of your prep, with peer sessions as a scheduled addition.

What round types does Exponent cover that Thita doesn't, or vice versa?

Exponent covers finance and SQL rounds that Thita doesn't specifically name. Thita covers low-level design, machine coding, and resume-based interviews that Exponent doesn't list. Data structures & algorithms, system design, behavioural, product management, and data science overlap on both.

Do I need a partner to use Thita?

No. Thita's AI interviewer starts immediately, without a scheduled partner — that's the main structural difference from Exponent's peer-matching model.

Which is better for a first-time interview candidate who's never done a mock interview before?

Either can work as a starting point, but the lower-friction option tends to get used more consistently in practice. If scheduling a partner feels like a barrier that might delay your first session by days, starting with an on-demand AI session removes that barrier, and you can add a peer session once you're comfortable with the format itself.

Bottom line

Pramp becoming Exponent didn't change the fundamental trade-off: a live human partner gives you a real, unscripted reaction, but it costs you scheduling and matching friction. Thita removes that friction and adds consistency and round coverage a peer platform doesn't have, at the cost of not being an actual person. For most candidates, the two aren't competing — they're complementary. Neither format alone will fully prepare you: the peer format gives you a texture of feedback an AI can't replicate, and the on-demand format gives you the repetition volume a shared calendar can't. Start a session with Thita's AI interviewer for your daily reps, and keep a live peer session in the mix for the specific value only a human interviewer provides.

Thita vs Pramp (Now Exponent): Which Should You Use?