Congress has lost its grip on funding the government - The Washington Post

The U. S. Congress is running on technical debt, and the last-minute budget patches are crashing the system. The Washington Post recently declared that "Congress has lost its grip on funding the government - The Washington Post" - a phrase that echoes across newsrooms and trading floors alike. But as a senior engineer watching the annual appropriations circus, I see something deeper: the legislative branch has become a legacy system that no one can refactor. The budget process - with its continuing resolutions (CRs), omnibus packages, and shutdown brinkmanship - is a textbook case of what happens when an organization abandons version control, accumulated years of spaghetti code, and refuses to adopt modern development practices.

In production software environments, we've learned that you cannot ship reliable code without a stable CI/CD pipeline, automated tests. And clear ownership of each module. Congress, by contrast, operates without any of these. It relies on a manual approval process that bottlenecks every September, then panics when the merge conflict of 12 appropriations bills crashes the government. The result is predictable: a last-minute CR that kicks the can, an omnibus bill that bundles thousands of pages of unrelated directives. And a growing pile of unfunded mandates - what engineers would call "dead code" that bloats the system.

This article isn't another political rant. It's an engineering analysis of a $6 trillion system that has lost its ability to execute its most basic function: allocate resources through a transparent, disciplined process. I'll walk through the analogies, cite concrete failures. And suggest what software teams can learn - and what Congress might borrow from Agile, CI/CD. And even open-source governance,

Why the Budget Process Is Like a Broken CI/CD Pipeline

Every healthy software team maintains a deployment pipeline: code is committed, built, tested in staging. And then promoted to production. Congress's budget pipeline is broken at every stage. And the first problem is branch managementInstead of merging 12 individual appropriations bills (like feature branches) into a coherent master, Congress often fails to merge any of them. By the fiscal year deadline, only a few bills have passed committee, let alone floor votes. The inevitable workaround is an omnibus - a single monolithic merge of 12 branches with thousands of undisclosed edits.

In an engineering team, such a merge would trigger a code review nightmare. The GAO has documented that omnibus bills frequently contain policy riders that haven't been vetted by relevant committees. This is the legislative equivalent of committing unreviewed code directly to production on a Friday evening. The Washington Post noted that "Congress has lost its grip on funding the government - The Washington Post" - and indeed, the grip slipped because the tooling (the budget committee calendars, the reconciliation process) is no longer fit for purpose. Without automated gates, manual review collapses under its own weight.

The second analogy is dependency managementModern applications rely on package managers to track external libraries. The federal budget depends on thousands of interlocking authorizations, mandatory spending formulas, and debt ceilings. When a subcommittee delays its markup, it cascades like an unhandled exception. The CR that follows is the equivalent of a runtime error catch-all - it keeps the system alive but silently corrupts data. The CBO estimates that reliance on CRs has wasted over $130 billion in efficiency losses since 2014, a number that grows with every patch.

The Congressional Budget Office: Your Legacy Mainframe That Still Works

If Congress were a tech company, the CBO would be its COBOL mainframe - critical, trusted. And terrifyingly difficult to replace. The CBO produces cost estimates and economic projections that underpin every funding decision. Yet its tools are decades old. The CBO still uses models written in FORTRAN for some tax simulations. And its dynamic scoring capabilities lag far behind private sector econometrics. In 2022, a GAO audit found that the CBO's IT systems had "significant security control deficiencies. "

Contrast this with how a well-run startup would approach fiscal modeling. They would invest in a modern data pipeline, perhaps using Apache Spark for large-scale simulation or a DuckDB-based query engine for rapid what-if analysis. The CBO, despite its talented staff, is constrained by legacy infrastructure. When the budget environment grows more complex (e, and g, dynamic effects of tax cuts, climate risk exposure), the CBO's outputs become less precise. This feeds back into the dysfunction: if you can't model the impact of a policy, you can't negotiate its trade-offs rationally.

Engineers working in government or adjacent nonprofits should note this lesson: a failed infrastructure upgrade is not just a technical debt - it's a systemic risk. Congress has lost its grip not only on the political will to fund the government but also on the data needed to make informed decisions. The CBO's latest long-term budget outlook shows deficits rising to 166% of GDP by 2054. Those numbers are only as reliable as the models feeding them. Until Congress modernizes its analytical stack, every budget negotiation operates with incomplete intelligence.

How Continuing Resolutions Mirror Accumulated Technical Debt

A continuing resolution (CR) is Congress's way of saying "we'll fix this later. " When a CR is passed, agencies operate at the previous year's funding levels - sometimes for months, sometimes for an entire fiscal year. This is identical to technical debt in software: you take a shortcut to meet a deadline, knowing it will cost more to fix later. The longer a CR remains in place, the more compound interest accrues. Agencies halt new hiring, delay procurement, and cancel non-critical projects. The DHS, for example, reported that in FY2024 a year-long CR forced a freeze on cybersecurity hiring at a time when threats were escalating.

In engineering teams, we have a concept of debt ceiling - a maximum allowed interest cost. Congress, however, imposes a literal debt ceiling that's entirely unrelated to the functional debt of the budget process. The two interact disastrously: a default crisis triggers a CR, which increases technical debt. Which makes it harder to pass a proper budget. Which leads to another default risk. From a codebase perspective, this is the classic "big ball of mud" pattern: no clear ownership, no refactoring budget. And mounting "TODO" comments that never get done.

The data backs this up, and according to the Government Accountability Office, from FY2010 to FY2022, Congress passed only one full budget on time (FY2017). Over 50% of budgets were enacted via CRs, often for months. Compare that to a development team whose deployment success rate is 50% - they would be fired. The Washington Post's headline is right: Congress has lost its grip, but the deeper problem is that nobody has committed tenure on the repo to clean up the accumulated mess.

The Failure of Iterative Development in Legislative Appropriations

Agile software development teaches us to deliver value in short iterations, with frequent stakeholder feedback. The budget process is supposed to be an annual cycle - a natural sprint length. But Congress has turned it into a death-march water-all with a single release date (September 30). When that release fails, they resort to emergency patches (CRs) that bypass the test suite (committee hearings). The iterative model that works for engineering fails because of two structural flaws: lack of vertical slicing and insufficient automation.

Vertical slicing in agile means delivering a full feature across all layers. In budgeting, vertical slicing would mean passing individual appropriations bills that cover a complete funding cycle for one agency, from policy guidance to spending limits. Instead, Congress tends to group everything horizontally - authorizations in one bill, appropriations in another, reconciliation in a third - which multiplies dependencies. The result is a combinatorial explosion of negotiations. When a single holdout senator can block an entire omnibus, the sprint is blocked by one work item.

Automation can't solve political impasse, but it can enforce discipline. For example, if the Budget Committee had a rule that failing to markup a bill by July 1 automatically triggers a 5% across-the-board cut (like an automated pipeline rollback), the incentives would change. Several think tanks have proposed "budget enforcement mechanisms" inspired by circuit breakers in software. The Committee for a Responsible Federal Budget outlines options like statutory PAYGO that function like a controlled shutdown when debt triggers are breached. Without such safeguards, the system continues to produce unreliable outputs, eroding public trust.

What Software Engineers Can Learn from the Budget Impasse

The dysfunction in Congress offers a cautionary tale for engineering teams of all sizes. The first lesson: never let your deployment cadence slip more than once. Once you skip a release, the pressure to include more features in the next one grows, leading to an unstable build. This is exactly what happens with CRs. The second lesson: document everything, especially the dependency graph. The federal budget has hundreds of overlapping programs with shared funding streams. When a CR freezes a funding level, it breaks the assumptions of downstream services. Engineers should maintain an up-to-date dependency matrix and run impact analyses before any funding freeze.

The third. And perhaps most important lesson, is about ownership and accountability. In software, we assign code owners who are responsible for reviewing changes to their modules. Congress has no equivalent. The House and Senate Appropriations Committees are nominally the owners. But they're bypassed by leadership when an omnibus is negotiated in secret. This creates a "tragedy of the commons" where every member adds earmarks but no one maintains the overall stability. Engineering teams that have seen their codebase degrade into unmaintainable state will recognize this pattern: too many cooks, no single point of quality control.

If I were to write a postmortem for the 2024 budget failure (which occurred when the last CR expired and a shutdown was averted by hours), it would read like many incident reports I've seen: "We had three weeks to merge 12 branches, conducted zero automated tests. And allowed senior leadership to override the merge review process. Result: production outage. " The pattern is so common that we have a name for it in the engineering world - Hero Culture. In Congress, the heroes are the Speaker and the Majority Leader who cobble together a deal at 3 a m. But like all hero culture, it creates a fragile, unrepeatable process.

The Role of AI in Streamlining Fiscal Oversight

Given the scale of the problem, could AI help Congress regain its grip? The answer is yes, but with caveats. Large language models (LLMs) like GPT-4 are already being tested by congressional staffers to summarize bills and identify conflicting provisions. The Congressgov API provides structured data on bills and votes. But the unstructured text is a mess of cross-references. AI can parse the interdependence of funding streams, flagging when a CR would violate an authorization statute. Tools like Copilot for Legislation aren't science fiction - the House Administration Committee piloted an AI tool in 2023 for drafting amendments.

More ambitiously, AI-driven simulation could let Congress model the effects of budget scenarios in real time. Imagine a table of 100 senators each running a "what if" game with a custom GPT trained on CBO data, exploring trade-offs between defense, healthcare. And climate. This is essentially a reinforcement learning environment for policy, and researchers at the Brookings Institution have explored how AI assistants could reduce information asymmetry, enabling more informed negotiations. However, the same tools could also be used to generate misleading analyses, magnifying partisan gridlock.

The engineering community has a responsibility here: open-source the budget simulation models, create transparent audit trails. And push for explainable AI. If the CBO were to adopt a modern machine learning pipeline (e, and g, using Prophet for time series forecasting of tax revenue), it would need to be as transparent as its current FORTRAN models. The alternative is dangerous - a black-box budget that even the experts can't untangle, accelerating the loss of grip that The Washington Post describes. Congress has lost its grip on funding the government - The Washington Post. But AI could either be the forklift upgrade or the next layer of spaghetti.

Can Open Source Governance Save Congress from Itself?

Open source software projects show that large, distributed groups can coordinate funding (via bounties and grants) and allocate resources efficiently. Could Congress adopt similar governance mechanisms? Several ideas are floating around: participatory budgeting, where citizens vote on funding for specific projects within a district; transparent ledger systems using blockchain to track every appropriations line item; modular authorization where agency funding is broken down into small, independently passed bills (like microservices) rather than omnibus monoliths.

While full open source governance is unlikely given constitutional constraints, the Budgeting for America Act (H, and r2747) proposes a bipartisan commission to study modernization. Engineers should pay attention: the bill includes provisions for "performance-based budgeting" that links funding to measurable outcomes - essentially KPIs for the government. This is a step toward the kind of data-driven resource allocation that DevOps teams practice.

But open source also teaches us that good governance requires a healthy community of maintainers. Congress currently lacks maintainer tenure: the average tenure of a House member is 8. 5 years, far shorter than the time needed to master the budget process. The resulting loss of institutional memory is like a codebase that loses its core contributors every election cycle. The Washington Post's headline captures the symptom, but the root cause is a lack of stable ownership. Until Congress invests in long-term staff expertise (protected from political churn), no amount of agile or AI tooling will fix the underlying disconnect.

A Call for Agile Budgeting: Time