JetBrains in 2026: Growth, AI, and How to Choose Your IDE
Hello HaWkers, JetBrains is back at the center of the conversation about developer tools. In its 2026 annual report, which summarizes 2025 results, the company reports 25.69% revenue growth over the previous year and more than 12.5 million recurring active users. At the same time, it describes a broad investment in agents and AI features integrated into its IDEs. Those figures matter, but they cannot tell you on their own whether to renew a license.
How much time must a tool save in your work to justify its price and the effort of switching? Here, we will read JetBrains' published figures without confusing growth with profit, examine what has changed in the product, and build a practical way to evaluate it. The goal is to move beyond the headline and reach a decision that fits your project, team, and budget.
What the official numbers actually show
The JetBrains report presents 25.69% annual revenue growth and more than 12.5 million recurring active users. The company also says its tools are used by teams at 88 of the Fortune Global 100 companies. These are indicators of scale and adoption, each with its own definition. A recurring active user, for example, is not necessarily a paying subscriber. Higher revenue does not automatically mean a higher margin.
Another figure deserves attention: according to the same document, JetBrains' AI tools reached a six-figure count of active paying users in the fourth quarter of 2025. The company reports 240% growth in this measure between the fourth quarter of 2024 and the fourth quarter of 2025. That suggests adoption of its AI features, but does not reveal what each customer paid, how many stayed afterward, or what it cost to provide those features.
It is tempting to combine a financial headline, a usage chart, and an opinion about IDE quality into one conclusion. Doing so erases important differences between revenue, net income, usage, and satisfaction. The annual highlights report is a company communication; it is not a replacement for full financial statements if you want to assess profit, cash, and expenses. If a news story mentions a loss, find the corresponding accounting document, the legal entity it covers, and the period before repeating the number as a consolidated fact about the entire group.
For you, the useful reading is more restrained: JetBrains has a large user base and continues to invest in developer tools. That is a reason to look closely at its products. It is not proof that a specific subscription pays off in your workflow. The decision depends on actual work such as navigating code, debugging, running tests, and reviewing changes.
What changed in the IDE experience
In the report, JetBrains describes Junie as a coding agent integrated into its IDEs and mentions AI Assistant as part of work inside the development environment. It also highlights unified distributions for IntelliJ IDEA and PyCharm. In its official explanation of the IntelliJ IDEA unified distribution, the company details the change to installation and licensing, with free and paid features inside one distribution.
There is a practical consequence: the editor becomes more than a place to type code. It can bring together inspections, refactoring, a terminal, database tools, and AI assistance. Integration may reduce context switching. It may also put more of your workflow in one vendor's hands. Neither effect should be assumed; both need to be observed in the project you maintain.
Consider a fix spanning an API, tests, and a database migration. An IDE might find usages, rename symbols, and take you to the failure in fewer steps. Yet your current editor might already handle that through configured extensions, without a new learning curve. If you use AI features, evaluate behavior on larger changes too: does the agent show a clear diff? Does it run the tests? Can you easily revert a bad change? A fast answer on screen is not the same as completed work.
The AI quota model explained by JetBrains is another item to check before buying. Included usage, limits, and extra charges can change the calculation once a team uses the tool every day. Consult the current pricing page when you purchase; this article deliberately avoids prices that may become outdated. When comparing products, use the total amount your organization will actually pay, including any extras you plan to use.
First, define the work that needs to improve
An honest comparison starts with tasks, not brands. Pick a representative repository and write down three actions you repeat: finding where a call originates, changing an interface used across several files, and debugging a test that fails intermittently. Record how long each takes, how many manual steps appear, and whether you had to undo mistakes. A demo in a small project may hide precisely the problems you face in a real monorepo.
If your team works across different services, include at least one example from each important language. Do not conclude that an IDE is best for everyone because it handled one Java project well. What matters is the mix of tasks performed by the person paying for the license or relying on a company-managed setup. Also observe startup time, indexing, and memory use on the machine that will actually run it.
Next, decide what counts as an improvement. Navigation time is one measure, but the quality of the change matters as much as speed. A refactor that appears to save ten minutes and introduces a regression creates a later cost. Record the test result, diff size, and review effort. For AI, use the same instruction, the same initial repository state, and the same acceptance criteria in each tool. Otherwise, your comparison measures differences in the experiment.
If you are setting up your workspace for the first time, read our development environment setup guide. It helps separate basic installation and configuration from the decision to buy a subscription. Make sure your terminal, runtime, tests, and version control work first. Then see whether the IDE speeds up a workflow you can already complete.
In practice: calculate subscription cost without inventing a return
Let's turn the decision into a simple calculation. The script below does not know JetBrains' price or your team's pay rates. You supply the numbers from your quote and a conservative estimate of hours saved each month. The result is a simulation, not a productivity promise. Save the file as custo-ide.mjs and run it with Node.js, passing the numbers as arguments.
// Usage: node custo-ide.mjs 40 3 25 2
// Arguments: monthly fee, hours saved, hourly cost, and adaptation hours.
const valores = process.argv.slice(2).map(Number);
if (valores.length !== 4 || valores.some(v => !Number.isFinite(v) || v < 0)) {
throw new Error('Enter four non-negative numbers.');
}
const [mensalidade, horasPoupadas, custoHora, horasAdaptacao] = valores;
const beneficioMensal = horasPoupadas * custoHora;
const custoInicial = horasAdaptacao * custoHora;
const saldoPrimeiroMes = beneficioMensal - mensalidade - custoInicial;
const saldoDepois = beneficioMensal - mensalidade;
console.log({ beneficioMensal, custoInicial, saldoPrimeiroMes, saldoDepois });The command's values are only sample data for testing the program. Replace all of them with numbers from your own situation. If the calculation works only when you assume a huge time saving, measure the work more carefully before buying. If the monthly bill includes AI, cloud services, or additional licenses, add those items to the subscription cost. Do not hide recurring expenses in a column called “details.”
Ask the reverse question
Would you keep using the tool if AI assistance were unavailable for a week? If the answer is no, you may primarily be buying an agent rather than an IDE. Compare data policies, usage limits, transparency of changes, and review quality in that case. If the answer is yes, identify the traditional features that justify the license. The distinction helps you avoid paying for an entire package when only one part solves your problem.
In practice: record tasks and compare medians
A short test can produce better evidence than an impression of speed. Create a CSV file with the columns ferramenta,tarefa,minutos,passou_testes. Complete each task in equivalent copies of the same project and record the time to finish, including fixes after running the tests. The code below groups the results and calculates the median for each tool and task. The median reduces the impact of an unusually slow run, but it cannot repair a poorly designed experiment.
// Save as medir-ide.mjs; usage: node medir-ide.mjs resultados.csv
import { readFile } from 'node:fs/promises';
const arquivo = process.argv[2];
if (!arquivo) throw new Error('Provide the results CSV file.');
const linhas = (await readFile(arquivo, 'utf8')).trim().split(/\r?\n/);
if (linhas.shift() !== 'ferramenta,tarefa,minutos,passou_testes') {
throw new Error('Unexpected header.');
}
const grupos = new Map();
for (const linha of linhas) {
const [ferramenta, tarefa, tempo, testes] = linha.split(',');
const minutos = Number(tempo);
if (!ferramenta || !tarefa || !Number.isFinite(minutos) || minutos < 0) {
throw new Error(`Invalid row: ${linha}`);
}
if (testes !== 'sim') continue; // Compare only completed tasks with passing tests.
const chave = `${ferramenta} / ${tarefa}`;
grupos.set(chave, [...(grupos.get(chave) ?? []), minutos]);
}
for (const [chave, tempos] of grupos) {
tempos.sort((a, b) => a - b);
const meio = Math.floor(tempos.length / 2);
const mediana = tempos.length % 2
? tempos[meio]
: (tempos[meio - 1] + tempos[meio]) / 2;
console.log(`${chave}: ${mediana} min (${tempos.length} completion(s))`);
}Use task names without commas: this deliberately small reader does not implement the full CSV format. Do not discard a failed attempt just because the script filters out rows without passing tests; count those failures separately. A tool that finishes quickly when it succeeds but often fails can be worse in practice. Record how often you needed help or had to open documentation as well.
In practice: set minimum standards for AI suggestions
Integrated AI must meet the same standards as any human change: readable code, runnable tests, and an opportunity for review. One cheap check is to look for unfinished-work markers in the proposed diff. The example below uses git diff to examine only added lines and flags TODO or FIXME. It cannot judge code quality; it merely stops an obvious reminder from being mistaken for finished work.
// Save as conferir-diff.mjs; run inside a Git repository.
import { execFileSync } from 'node:child_process';
const diff = execFileSync('git', ['diff', '--unified=0'], { encoding: 'utf8' });
const adicionadas = diff.split('\n').filter(linha => linha.startsWith('+') && !linha.startsWith('+++'));
const pendencias = adicionadas.filter(linha => /\b(TODO|FIXME)\b/i.test(linha));
if (pendencias.length) {
console.error('Review the newly added pending items:');
for (const linha of pendencias) console.error(linha);
process.exitCode = 1;
} else {
console.log('No TODO or FIXME marker was added.');
}A check like this can become part of your review routine whether you use Junie, another agent, or only an editor. It will not find bugs, leaked secrets, or weak tests. For those, keep project-specific tests, static analysis, and security review suited to your project. The value of AI integration lies in reducing effort while keeping the path from request to change to result visible.
If the agent produces many changes at once, prefer smaller requests and frequent checkpoints. Read the touched files, run the relevant test suite, and understand why behavior changed. An IDE that makes the diff easier to navigate can make that review less tiring; measure that benefit too. The number of accepted suggestions is a poor metric if they cause rework or the team stops understanding its own code.
How to decide as a team without making preference a rule
Different people value different features. Someone maintaining an older service may need safe refactoring. Someone working on the frontend may prioritize previews, formatting, and browser tests. Someone handling data may spend most of the day in queries and schemas. One tool policy works only when the team's tasks and constraints have been heard. Leadership should ask which outcomes need to improve and how much freedom the team needs to keep.
Build a small matrix with frequent tasks, total cost, quality of assistance, performance on your machines, and support for the languages you use. Assign weights to each criterion before testing. If you decide the weights after seeing the result, the matrix becomes a justification for a decision already made. For a company, add license administration, data policy, and the cost of leaving the tool.
The report portrays a company investing in AI and its ecosystem. For users, that may mean more options and integration. For managers, it means prices, limits, and governance deserve regular review. Repeat your small experiment when your workflow changes or when it is time to renew the commercial agreement. A sound decision today does not have to become a permanent rule.
Looking ahead: growth provides context, productivity needs proof
The 25.69% revenue growth and the 12.5 million recurring active users help explain why JetBrains remains relevant. The growth in paying AI users indicates real interest in assisted development. None of those figures directly measures the time you will save in your repository. They also do not, by themselves, answer questions about profit, infrastructure costs, or the quality of any particular product.
My recommendation is simple: use the report to understand the company's direction, then use a controlled test to decide on the license. Compare tasks you actually perform, include the cost of adapting, count failures, and inspect how AI behaves during review. If the tool delivers consistent value, the evidence supports your choice. If it does not, you will have a clear way to explain why without relying on brand loyalty.
The market for IDEs and coding agents is still changing quickly. Today, choose a task that regularly takes time, record the result in your current environment, and repeat the test with the alternative you are considering. An imperfect but honest measurement is more useful than assuming that revenue growth or an impressive demo determines the future of your workflow.
Let's go! 🦅
📚 Want to Keep Up With What Is Coming?
This article covered JetBrains' results and a practical way to choose an IDE, but the ecosystem changes every week and not every development becomes an article here.
On X, I share what I am testing, behind-the-scenes notes from my projects, and news that appears before it becomes a blog post.
Follow Me There
💡 Daily content about development, careers, and the tools I actually use