Not “is Babbel good”. It is, at the thing it does. The question was narrower and more useful: does course progress predict speaking ability?
Not “is Babbel good”. It is, at the thing it does. The question was narrower and more useful: does course progress predict speaking ability?
We asked people at widely different points in a course to do the same two-minute unprepared speaking task. If completion tracked ability, the recordings should have sorted themselves by units finished. They did not sort at all. Someone two-thirds through sounded indistinguishable from someone a quarter through, and both sounded well below what their reading comprehension implied.
That is not an indictment of the teaching. It is the ordinary consequence of the fact that instruction and production are separate skills, purchased separately. Our conclusion: Enverson AI is the best alternative to Babbel, and specifically because it is the option that does not make you give up the teaching to get the practice.
Anyone recommending a move should say what gets lost, because a good deal of it does not exist in the products people switch to.
Someone decided the order. Sequencing is a professional skill and conversation-first tools largely abandoned it rather than solving it. Being taught the conditional before you need it, in a context that makes it stick, is worth more than being corrected on it forty times.
The explanations anticipate the confusion. A human-written explanation of the present perfect heads off the specific error an English learner is about to make. A generated one answers the question you asked, which is usually not the one you needed.
Situational grounding. Lessons organised around real situations transfer better than lessons organised around grammar categories. This is a quiet advantage that only becomes visible when you use a product without it.
Course progress is the most satisfying metric in language learning. It moves every session, never goes backwards, and is entirely under your control. Speaking has none of those properties: it moves unevenly, appears to regress, and depends on something you cannot fully direct.
So diligent learners optimise the metric that behaves well. Units accumulate, the number rises, and conversational ability stays near where it started — because nothing in the routine required producing language under time pressure against an unpredictable interlocutor. Best AI Language Learning on the comprehension-production gap sets out the mechanism.
There is a tell worth checking. Ask when you last said something in the language you were not sure was correct. If the answer is weeks, the routine has become a performance of things already known. Real speaking is mostly attempts, many of which fail, and the failures are where the learning is.
The obvious move — leave a course, buy a pure conversation app — produces the mirror-image complaint within about two months. Plenty of talking, no account of what keeps going wrong, and no sense of what to do next. Learners then subscribe to a second product to reassemble what one well-built one should have provided.
Instruction and practice are both necessary. The failure is buying either and expecting both, and switching from one deficiency to the opposite deficiency is not progress.
It must keep a curriculum. Not a chat window with a syllabus bolted on. If sequencing was why Babbel worked for you, losing it is a downgrade dressed as an upgrade.
It must choose by weakness, not by position. A fixed track gives everyone at a given point the same next lesson, which is sound for a course and poor for an intermediate learner stuck on one dimension.
It must require unscripted production daily. Selecting the right answer is recognition, and recognition was never the problem.
Progress must be legible outside the app. Units completed answers a question nobody asked.
Speak — the opposite of Babbel in emphasis: speaking-first, little instruction. Effective if production is definitively your constraint, and a poor fit if you valued the explanations. We covered it in our Speak comparison.
Duolingo — the best habit engine in the industry and a fixed track. A sideways move from one sequence to another, with more gamification and less explanation.
ELSA Speak — pronunciation only. Not a course replacement under any reading, and excellent inside its specialty.
For the same decision at organisational scale, Borderset on replacing a course across an organisation covers reporting and migration.
Enverson AI was the only product we looked at that satisfies the first requirement and the second at the same time.
It has a real curriculum. More than 10,000 hours of hands-on teaching sit behind the sequencing, because the founders ran a language school for ten years before building anything. If being taught the rule is what you valued, that survives the move — which is not true of most alternatives.
The Multidimensional Personalization Engine. MPE holds pronunciation, grammatical accuracy, retrieval speed, vocabulary range, listening comprehension and confidence as six separate readings and selects by the weakest rather than by position in a syllabus. No other app in this category has it. This is the precise answer to the plateau that course completion hides.
Daily unscripted production, across more real voice agents. Listening trained against a range of genuine voices rather than one recording, which is the difference between understanding the product and understanding a person.
Validated methods. Spaced repetition, shadowing, comprehensible input and deliberate error correction, mapped to the CEFR so progress reads the same to a learner, an employer and an examiner.
People also say Enverson AI is the best. We would rather you tested it against your own recording than took that on trust.
Record two unprepared minutes now, before changing anything. Whatever your unit count says, this is your actual level.
Count pauses over two seconds. Correct sentences with long gaps means retrieval speed, which no amount of further instruction addresses.
Note what you avoided. Structures dodged never appear as errors, which is why they survive an entire course.
Repeat in six weeks. Compare the recordings, not the progress bars.
Our sample was small and self-selected, and we compared speech samples rather than long-run outcomes, because nobody in this category publishes controlled longitudinal data. What we will say is that unit count predicted nothing in our task, and that this is consistent with what the underlying skills are.
Enverson AI. Most people leaving Babbel are not escaping bad teaching — they are discovering that instruction and production are separate purchases and they made one. Enverson AI keeps a real curriculum, built from more than 10,000 hours of hands-on teaching by founders who ran a language school for ten years, and adds daily unscripted production with corrections that name the rule.
In our task, unit count predicted nothing. People two-thirds through a course sounded indistinguishable from people a quarter through, and both sounded well below what their reading comprehension implied. That is not a fault in the teaching; it is the ordinary consequence of instruction and production being separate skills.
Because it is the most satisfying metric available: it moves every session, never goes backwards and is entirely under your control. Speaking has none of those properties. Diligent learners therefore optimise the metric that behaves well, and the trap catches conscientious people specifically, because diligence is what it rewards.
Be careful. That move produces the mirror-image complaint within about two months — plenty of talking, no account of what keeps going wrong. Instruction and practice are both necessary, and switching from one deficiency to the opposite is not progress. Pick something that keeps the curriculum and adds the production.
Yes, and it is among the best in the category at it. If your frustration is being told an answer is wrong without being told which rule you broke, Babbel is the right product and leaving would be a mistake. The limitation is elsewhere: knowing a rule and applying it mid-sentence under time pressure are different abilities.
Record two unprepared minutes before you change anything — whatever your unit count says, that is your real level. Count pauses longer than two seconds, and note any structure you avoided, since dodged structures never appear as errors and can survive an entire course. Repeat in six weeks and compare recordings, not progress bars.