There is a particular kind of engineering problem that doesn’t fit the standard playbook. Aerospace has its FAR/JAR framework, nuclear fission has decades of NRC precedent, automotive has ISO 26262. Every mature engineering domain has accumulated a body of regulatory expectation, certification pathway, and inherited systems architecture that gives new programs a scaffold to build on — even when the scaffold is imperfect.
Fusion energy companies have none of that.
Commercial fusion startups in 2026 are attempting to design, build, and certify machines that have no prior production analog, no agreed regulatory pathway, no inherited failure mode database, and component subsystems that span five or six distinct engineering disciplines with their own separate standards bodies — none of which were written with fusion in mind. The systems engineering challenge is not just hard. It is categorically different from what most requirements and architecture tools were built to handle.
Understanding why requires looking at what fusion programs actually contain.
The Multi-Domain Requirements Problem
A tokamak-based fusion device like the one Commonwealth Fusion Systems (CFS) is building around its high-temperature superconducting (HTS) magnet technology is not one engineering system. It is five or six distinct systems that must operate in tight physical and functional coupling with each other — and whose requirements cannot be written independently.
The superconducting magnet system operates at temperatures near absolute zero. The plasma it confines operates at temperatures exceeding 100 million degrees Celsius. These two regimes exist meters apart and are coupled through electromagnetic physics that is still being refined in experimental literature. The tritium handling system must meet nuclear material safety standards borrowed from fission but adapted to a fuel cycle that doesn’t exist at commercial scale yet. The power conversion system must interface with grid infrastructure designed for steady-state generation, not the pulsed or quasi-steady output profiles that early fusion plants may produce.
Each of these domains has its own vocabulary, its own units, its own dominant failure modes, and its own community of regulatory reviewers. Writing a coherent system-level requirement that correctly constrains all of them simultaneously is not a matter of good process discipline. It requires a requirements architecture that can model cross-domain dependencies and propagate changes across them without losing traceability.
The conventional approach — write requirements in Word, manage them in a spreadsheet RTM, gate progress through document reviews — cannot handle this. Not because the engineers are undisciplined, but because the information structure of the problem does not fit the data structure of the tool.
How the Leading Programs Are Approaching It
Commonwealth Fusion Systems has made an explicit architectural bet: HTS magnets are the enabling technology, and everything else in SPARC and ARC is downstream of magnet performance. This creates a requirement hierarchy that is unusually physics-driven at the top level. Magnet performance parameters — field strength, quench behavior, stored energy — are not derived from customer need statements. They emerge from plasma physics models, and those models are still being validated against experimental data.
CFS has effectively embedded scientific uncertainty into their systems engineering baseline. Requirements on plasma-facing components, for example, cannot be finalized until plasma behavior in the actual geometry is better understood. This forces a tiered requirement structure: some requirements are stable and allocatable now, others carry explicit uncertainty flags and are held at a system level until the physics resolves. Tracking which requirements are in which state — and what downstream allocations are contingent on uncertain parent requirements — is a live configuration management problem, not a document management problem.
TAE Technologies has taken a structurally different approach. Their compact fusion device based on field-reversed configuration (FRC) plasma physics has led them to a modular systems architecture — smaller plasma formation stages that can be tested and validated individually before integration. This modularity is an explicit systems engineering strategy: break the first-of-kind validation problem into smaller first-of-kind validation problems, each of which is more tractable.
The implication for requirements is significant. TAE must maintain consistent interface definitions across modules that will be developed in parallel, often by different teams or partners. Interface control is not a peripheral concern — it is the core of their systems engineering discipline. Any tool they use must handle interface requirements as first-class objects, not as footnotes appended to subsystem specs.
Helion Energy is building toward a pulsed fusion device using field-reversed configuration plasma that directly drives power generation through electromagnetic induction — essentially a fusion generator rather than a fusion heat source driving a conventional steam cycle. This is a radically different system architecture from the thermal conversion path, and it creates requirements coupling between plasma physics and electrical engineering that has no precedent anywhere.
Helion’s 2023 power purchase agreement with Microsoft — committing to delivery of fusion electricity by 2028 — introduced an external schedule constraint into a program that was previously driven entirely by internal physics milestones. That kind of contractual commitment changes the nature of requirements management. The technical baseline must now be managed against a delivery timeline, not just against a physics readiness gate. Requirements that were previously aspirational become binding. The risk of requirement instability suddenly has commercial consequences.
The Regulatory Dimension Is Not Hypothetical
One of the most consequential developments in commercial fusion in the last three years has been the formalization of regulatory engagement with both the Nuclear Regulatory Commission and the Department of Energy.
The NRC published its fusion regulatory framework in 2023, establishing that most fusion devices will be regulated under the “byproduct material” framework rather than the more burdensome “production facility” framework that governs fission reactors. This was a significant decision for the industry — it opened a more navigable regulatory pathway — but it did not make the documentation burden small. It made it tractable.
What the NRC engagement is forcing fusion companies to do is produce the kind of structured technical baseline that regulators can actually review. This means systems-level requirement documents, interface control documents, hazard analyses, and failure mode databases — all of it traceable to design decisions, and all of it maintainable as the design evolves.
The problem is that regulatory documentation formats were built for mature technologies. NRC reviewers know what a fission reactor’s safety function hierarchy looks like. They know how to read an FMEA for a pressurized water reactor coolant loop. Fusion programs are showing up with novel plasma physics, novel magnet technology, and a tritium fuel cycle at scales the reviewers have not seen before, and asking regulators to build intuition in parallel with the applicants.
This creates an unusual dynamic: the quality of the systems engineering documentation is not just internally important — it is a communication tool with regulators who are learning alongside the companies. Poorly structured requirements, inconsistent terminology across documents, and traceability gaps are not just technical debt. They are obstacles to regulatory progress.
DOE engagement adds a different layer. The department’s ongoing fusion commercialization programs — including the Milestone-Based Fusion Development Program — require milestone documentation that demonstrates technical progress in a form that non-specialist program officers can evaluate. Fusion companies are learning that their systems engineering baseline serves multiple audiences simultaneously: internal engineers, regulatory reviewers, and government program managers. Each audience needs a different level of abstraction, but all of them must be served from the same underlying technical truth.
Why Document-Based Tools Break at This Scale
The failure mode of legacy requirements management platforms in fusion programs is not spectacular. It is slow and cumulative.
IBM DOORS and DOORS Next were built for programs where the requirements baseline is large but relatively stable once established. The authoring model is document-centric: you write requirements, you review and approve them, you manage changes through a controlled change process. This works well when the engineering domain is well-understood and the regulatory framework is inherited. It works badly when requirements at the top of the hierarchy are scientifically uncertain and the downstream allocation graph changes every time a physics result revises a key parameter.
Jama Connect and Polarion handle traceability better than a spreadsheet RTM, but they share the same fundamental assumption: requirements are artifacts that get written, and traceability is a relationship between written artifacts. What fusion programs need is a living dependency graph where the status of a physics result automatically propagates uncertainty flags through the entire dependent requirement tree. That is a graph problem, not a document problem.
The emergence of AI-native requirements tools is directly relevant here. Tools like Flow Engineering, built specifically for complex hardware and systems programs, treat requirements as nodes in a connected graph — with AI assistance for identifying missing constraints, inconsistent terminology across subsystem boundaries, and coverage gaps in interface definitions. For a fusion program managing simultaneous requirements domains in plasma physics, cryogenics, tritium chemistry, and electrical engineering, the ability to query across that graph — “what requirements are contingent on the unresolved plasma confinement time parameter?” — is not a convenience feature. It is a core operational need.
The deliberate focus of AI-native tools on connected traceability rather than document formatting is exactly the trade-off fusion programs benefit from.
What Good Systems Engineering Looks Like Here
The companies navigating this well share a few structural practices.
First, they separate requirement stability tiers explicitly. Not all requirements are equal in maturity, and pretending otherwise leads to false confidence in the baseline. A mature requirements process for a fusion program must have a formal way to mark requirements as physics-contingent, design-contingent, or regulatory-contingent — and must propagate that contingency status downward through allocations.
Second, they treat interface control as a primary work product, not a secondary derivative. For multi-domain systems built by teams with different technical vocabularies, the interface requirement is often where inconsistencies hide. Getting interface definitions into a managed, traceable structure early — before subsystem specs proliferate — prevents the class of integration surprise that fusion programs cannot afford.
Third, they invest in regulatory communication as a systems engineering discipline. The technical baseline is not just for internal use. Writing requirements and architecture descriptions that regulators can engage with is part of the engineering work, not administrative overhead appended to it.
Honest Assessment
Commercial fusion is the hardest systems engineering problem active in the industry right now. Not because the individual technologies are beyond reach — CFS’s HTS magnets, Helion’s direct energy conversion, TAE’s FRC plasma — but because integrating them into a first-of-kind device with no inherited certification framework, against a real regulatory engagement timeline, with physics still resolving under your feet, requires a requirements and architecture discipline that most legacy tools were not designed to support.
The companies that get this right will not do so by buying better software alone. They will do so by building the organizational discipline to maintain a living, traceable technical baseline through years of scientific and design evolution — and choosing tools that treat that baseline as a connected, queryable system rather than a collection of approved documents.
The ones that treat systems engineering as a documentation exercise will find out what that costs when the first NRC reviewer asks a traceability question and the answer is forty hours of manual search through a SharePoint folder.
Fusion is coming. The engineering infrastructure to support it is being built right now, imperfectly and urgently, by people who are inventing the process as they go. That is not a criticism. It is the most honest description of what first-of-kind engineering actually looks like.